[FreeCourseSite.com] Udemy - Complete 2022 Data Science & Machine Learning Bootcamp

磁力链接/BT种子名称

[FreeCourseSite.com] Udemy - Complete 2022 Data Science & Machine Learning Bootcamp

磁力链接/BT种子简介

种子哈希：6c07de4db88f94a690998017789362b5165a8802
文件大小： 12.53G
已经下载：2801次
下载速度：极快
收录时间：2023-12-20
最近下载：2025-09-06

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:6C07DE4DB88F94A690998017789362B5165A8802
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 她趣 TikTok成人版 PornHub 听泉鉴鲍 草榴社区 哆哔涩漫 呦乐园 萝莉岛

最近搜索

文件列表

  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 240.6 MB
  • 12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image.mp4 220.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 210.7 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix.mp4 202.6 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate.mp4 199.4 MB
  • 03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports.mp4 195.9 MB
  • 12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server.mp4 183.9 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 183.7 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions.mp4 182.3 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout.mp4 182.3 MB
  • 12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas.mp4 181.1 MB
  • 12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas.mp4 167.0 MB
  • 12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic.mp4 165.9 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 159.9 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts.mp4 159.4 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary.mp4 156.7 MB
  • 12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images.mp4 155.0 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn.mp4 152.8 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 152.3 MB
  • 03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation.mp4 144.8 MB
  • 12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling.mp4 143.4 MB
  • 03 - Python Programming for Data Science and Machine Learning/014 Working with Python Objects to Analyse Data.mp4 142.0 MB
  • 12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV.mp4 139.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/027 Making Predictions (Part 1) MSE & R-Squared.mp4 132.7 MB
  • 03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods.mp4 131.4 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning.mp4 130.4 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/023 Model Simplification & Baysian Information Criterion.mp4 125.5 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture.mp4 116.0 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/011 Visualising Correlations with a Heatmap.mp4 113.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/004 Clean and Explore the Data (Part 2) Find Missing Values.mp4 112.7 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/013 [Python] - Loops and Performance Considerations.mp4 111.8 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/028 Styling the Word Cloud with a Mask.mp4 111.1 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/022 Understanding VIF & Testing for Multicollinearity.mp4 110.5 MB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python.mp4 110.2 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/002 Create a Full Matrix.mp4 109.9 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/011 [Python] - Generator Functions & the yield Keyword.mp4 109.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/007 Working with Index Data, Pandas Series, and Dummy Variables.mp4 108.8 MB
  • 12 - Serving a Tensorflow Model through a Website/002 Saving Tensorflow Models.mp4 108.7 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/006 Making Predictions using InceptionResNet.mp4 108.2 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/011 Understanding Partial Derivatives and How to use SymPy.mp4 107.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4 107.6 MB
  • 03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series.mp4 106.3 MB
  • 03 - Python Programming for Data Science and Machine Learning/010 [Python] - Functions - Part 2 Arguments & Parameters.mp4 104.3 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/030 Styling Word Clouds with Custom Fonts.mp4 104.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4 104.0 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/009 Tensorboard Summaries and the Filewriter.mp4 103.5 MB
  • 12 - Serving a Tensorflow Model through a Website/015 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 103.2 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 101.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/002 Gathering Email Data and Working with Archives & Text Editors.mp4 100.7 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/014 Reshaping and Slicing N-Dimensional Arrays.mp4 99.7 MB
  • 12 - Serving a Tensorflow Model through a Website/004 Converting a Model to Tensorflow.js.mp4 98.2 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm.mp4 97.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/019 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 97.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/035 Sparse Matrix (Part 2) Data Munging with Nested Loops.mp4 96.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries.mp4 94.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 94.5 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/010 Understanding the Tensorflow Graph Nodes and Edges.mp4 93.8 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/006 Joint & Conditional Probability.mp4 92.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/009 Reading Files (Part 2) Stream Objects and Email Structure.mp4 92.0 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/013 Prediction and Model Evaluation.mp4 91.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/021 Removing HTML tags with BeautifulSoup.mp4 90.8 MB
  • 12 - Serving a Tensorflow Model through a Website/003 Loading a SavedModel.mp4 89.2 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/012 Techniques to Style Scatter Plots.mp4 87.9 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/010 Calculating Correlations and the Problem posed by Multicollinearity.mp4 86.5 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/007 Coding Challenge Solution Using other Keras Models.mp4 86.0 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/025 Residual Analysis (Part 1) Predicted vs Actual Values.mp4 85.4 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/020 Improving the Model by Transforming the Data.mp4 85.4 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/004 Exploring the CIFAR Data.mp4 85.1 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/003 Costs and Disadvantages of Neural Networks.mp4 80.3 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 80.3 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 79.7 MB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/005 Analyse and Evaluate the Results.mp4 79.1 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/038 Checkpoint Understanding the Data.mp4 78.2 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/021 Running Gradient Descent with a MSE Cost Function.mp4 77.9 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/008 TensorFlow Sessions and Batching Data.mp4 77.2 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/031 Create the Vocabulary for the Spam Classifier.mp4 73.5 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/016 Data Visualisation (Part 1) Pie Charts.mp4 73.5 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/004 Preprocessing Image Data and How RGB Works.mp4 72.6 MB
  • 12 - Serving a Tensorflow Model through a Website/005 Introducing the Website Project and Tooling.mp4 72.1 MB
  • 03 - Python Programming for Data Science and Machine Learning/015 [Python] - Tips, Code Style and Naming Conventions.mp4 70.4 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/011 Name Scoping and Image Visualisation in Tensorboard.mp4 70.1 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/012 Implementing Batch Gradient Descent with SymPy.mp4 68.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4 66.8 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/003 Count the Tokens to Train the Naive Bayes Model.mp4 66.7 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/005 Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4 64.3 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.mp4 64.3 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/005 Understanding the Power Rule & Creating Charts with Subplots.mp4 62.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/034 Sparse Matrix (Part 1) Split the Training and Testing Data.mp4 60.9 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/017 Transposing and Reshaping Arrays.mp4 60.8 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/025 [Python] - Logical Operators to Create Subsets and Indices.mp4 60.2 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4 59.5 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/024 Advanced Subsetting on DataFrames the apply() Function.mp4 57.9 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/018 Implementing a MSE Cost Function.mp4 57.2 MB
  • 03 - Python Programming for Data Science and Machine Learning/011 [Python] - Functions - Part 3 Results & Return Values.mp4 56.8 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/001 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 56.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/007 Bayes Theorem.mp4 53.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/026 Word Clouds & How to install Additional Python Packages.mp4 52.5 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 52.0 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.mp4 51.7 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/005 Importing Keras Models and the Tensorflow Graph.mp4 51.6 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/021 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 51.4 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/019 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 51.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/002 Gathering the Boston House Price Data.mp4 49.9 MB
  • 03 - Python Programming for Data Science and Machine Learning/005 [Python] - Variables and Types.mp4 49.9 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/002 Joint Conditional Probability (Part 1) Dot Product.mp4 49.3 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/004 LaTeX Markdown and Generating Data with Numpy.mp4 49.3 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/029 Solving the Hamlet Challenge.mp4 49.1 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/020 Word Stemming & Removing Punctuation.mp4 48.9 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/014 Cleaning Data (Part 2) Working with a DataFrame Index.mp4 48.8 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/003 Joint Conditional Probablity (Part 2) Priors.mp4 48.0 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/007 Interacting with the Operating System and the Python Try-Catch Block.mp4 48.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/027 Creating your First Word Cloud.mp4 47.8 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/016 How to Shuffle and Split Training & Testing Data.mp4 47.3 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/015 Saving a JSON File with Pandas.mp4 45.5 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/016 Introduction to the Mean Squared Error (MSE).mp4 45.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/005 Visualising Data (Part 1) Historams, Distributions & Outliers.mp4 44.7 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/007 False Positive vs False Negatives.mp4 43.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/033 Coding Challenge Find the Longest Email.mp4 43.1 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/008 Understanding Descriptive Statistics the Mean vs the Median.mp4 43.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/017 Data Visualisation (Part 2) Donut Charts.mp4 42.9 MB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/002 Gather & Clean the Data.mp4 42.8 MB
  • 01 - Introduction to the Course/001 What is Machine Learning.mp4 42.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/017 Running a Multivariable Regression.mp4 42.2 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/011 Model Evaluation and the Confusion Matrix.mp4 42.0 MB
  • 01 - Introduction to the Course/002 What is Data Science.mp4 41.8 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/002 Getting the Data and Loading it into Numpy Arrays.mp4 41.6 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/008 Reading Files (Part 1) Absolute Paths and Relative Paths.mp4 41.5 MB
  • 03 - Python Programming for Data Science and Machine Learning/002 Mac Users - Install Anaconda.mp4 41.0 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/003 Introduction to Cost Functions.mp4 40.9 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/005 What is a Tensor.mp4 39.7 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/006 Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4 39.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/018 Introduction to Natural Language Processing (NLP).mp4 39.3 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/012 Create a Pandas DataFrame of Email Bodies.mp4 39.2 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/004 Making Predictions Comparing Joint Probabilities.mp4 38.9 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/022 Visualising the Optimisation on a 3D Surface.mp4 37.3 MB
  • 12 - Serving a Tensorflow Model through a Website/001 What you'll make.mp4 37.2 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/005 Calculate the Token Probabilities and Save the Trained Model.mp4 37.0 MB
  • 03 - Python Programming for Data Science and Machine Learning/006 [Python] - Lists and Arrays.mp4 36.8 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/009 The Precision Metric.mp4 36.1 MB
  • 12 - Serving a Tensorflow Model through a Website/017 Publish and Share your Website!.mp4 34.9 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/001 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 34.3 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/015 Concatenating Numpy Arrays.mp4 34.1 MB
  • 03 - Python Programming for Data Science and Machine Learning/001 Windows Users - Install Anaconda.mp4 33.7 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/002 Installing Tensorflow and Keras for Jupyter.mp4 33.5 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/015 Understanding Multivariable Regression.mp4 33.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/001 How to Translate a Business Problem into a Machine Learning Problem.mp4 32.5 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/010 Extracting the Text in the Email Body.mp4 32.0 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/001 Defining the Problem.mp4 31.5 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 30.8 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/005 The Accuracy Metric.mp4 30.1 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/006 Coding Challenge Prepare the Test Data.mp4 30.0 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/024 How to Analyse and Plot Regression Residuals.mp4 29.4 MB
  • 03 - Python Programming for Data Science and Machine Learning/009 [Python] - Functions - Part 1 Defining and Calling Functions.mp4 28.7 MB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/001 Introduction to Linear Regression & Specifying the Problem.mp4 27.8 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/022 Creating a Function for Text Processing.mp4 27.6 MB
  • 12 - Serving a Tensorflow Model through a Website/011 Data Pre-Processing for Tensorflow.js.mp4 26.8 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/004 Sum the Tokens across the Spam and Ham Subsets.mp4 25.6 MB
  • 12 - Serving a Tensorflow Model through a Website/008 Adding a Favicon.mp4 25.5 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18190700-SpamData.zip 23.9 MB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/18190704-SpamData.zip 23.4 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/018 How to Calculate the Model Fit with R-Squared.mp4 22.5 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18190724-SpamData.zip 22.3 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/003 Gathering the CIFAR 10 Dataset.mp4 21.6 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/003 Data Exploration and Understanding the Structure of the Input Data.mp4 21.6 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/001 Set up the Testing Notebook.mp4 20.9 MB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/001 Solving a Business Problem with Image Classification.mp4 20.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/003 How to Add the Lesson Resources to the Project.mp4 19.9 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/037 Coding Challenge Solution Preparing the Test Data.mp4 19.8 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/008 The Recall Metric.mp4 19.3 MB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/010 The F-score or F1 Metric.mp4 17.3 MB
  • 03 - Python Programming for Data Science and Machine Learning/003 Does LSD Make You Better at Maths.mp4 16.4 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/032 Coding Challenge Check for Membership in a Collection.mp4 15.6 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/18194656-MNIST.zip 15.5 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/001 What's Coming Up.mp4 13.5 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/009 Introduction to Correlation Understanding Strength & Direction.mp4 13.5 MB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/004 The Intuition behind the Linear Regression Model.mp4 13.5 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/002 How a Machine Learns.mp4 11.0 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/005 Basic Probability.mp4 9.9 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/019 Introduction to Model Evaluation.mp4 7.7 MB
  • 11 - Use Tensorflow to Classify Handwritten Digits/001 What's coming up.mp4 5.5 MB
  • 12 - Serving a Tensorflow Model through a Website/21028926-math-garden-stub-complete.zip 4.3 MB
  • 12 - Serving a Tensorflow Model through a Website/21028932-math-garden-stub-12.12-checkpoint.zip 4.3 MB
  • 05 - Predict House Prices with Multivariable Linear Regression/18179918-04-Multivariable-Regression.ipynb.zip 3.7 MB
  • 12 - Serving a Tensorflow Model through a Website/21028876-MNIST-Model-Load-Files.zip 3.0 MB
  • 03 - Python Programming for Data Science and Machine Learning/18204473-12-Rules-to-Learn-to-Code.pdf 2.4 MB
  • 12 - Serving a Tensorflow Model through a Website/21028894-TFJS.zip 1.6 MB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/18179908-03-Gradient-Descent.ipynb.zip 1.2 MB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18179924-06-Bayes-Classifier-Pre-Processing.ipynb.zip 1.0 MB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18180490-09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 585.6 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18188466-TF-Keras-Classification-Images.zip 513.1 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/9246634-cost-revenue-dirty.csv 383.7 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18180294-07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 248.9 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/18187728-10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 123.0 kB
  • 01 - Introduction to the Course/18162714-ML-Data-Science-Syllabus.pdf 106.5 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/9249290-cost-revenue-clean.csv 93.0 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/18175146-01-Linear-Regression-complete.ipynb.zip 77.1 kB
  • 12 - Serving a Tensorflow Model through a Website/21028914-math-garden-stub.zip 45.1 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/18175084-01-Linear-Regression-checkpoint.ipynb.zip 38.5 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm_en.vtt 38.5 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1)_en.vtt 38.1 kB
  • 03 - Python Programming for Data Science and Machine Learning/18179882-02-Python-Intro.ipynb.zip 37.3 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix_en.vtt 36.3 kB
  • 12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas_en.vtt 36.2 kB
  • 12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV_en.vtt 35.3 kB
  • 12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling_en.vtt 34.7 kB
  • 12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server_en.vtt 34.5 kB
  • 12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic_en.vtt 34.4 kB
  • 12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas_en.vtt 34.0 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate_en.vtt 33.3 kB
  • 12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image_en.vtt 32.9 kB
  • 03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports_en.vtt 32.2 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary_en.vtt 31.0 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions_en.vtt 30.9 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn_en.vtt 30.0 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2)_en.vtt 29.7 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout_en.vtt 27.7 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python_en.vtt 27.6 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture_en.vtt 26.8 kB
  • 03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods_en.vtt 26.5 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques_en.vtt 25.7 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques_en.vtt 25.6 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning_en.vtt 25.2 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module_en.vtt 25.1 kB
  • 03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series_en.vtt 25.0 kB
  • 12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images_en.vtt 24.8 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/011 Name Scoping and Image Visualisation in Tensorboard_en.vtt 24.4 kB
  • 03 - Python Programming for Data Science and Machine Learning/014 Working with Python Objects to Analyse Data_en.vtt 24.1 kB
  • 12 - Serving a Tensorflow Model through a Website/003 Loading a SavedModel_en.vtt 23.7 kB
  • 03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation_en.vtt 23.6 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts_en.vtt 23.1 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/022 Understanding VIF & Testing for Multicollinearity_en.vtt 22.8 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/007 Interacting with the Operating System and the Python Try-Catch Block_en.vtt 22.0 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/009 Tensorboard Summaries and the Filewriter_en.vtt 21.8 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/011 Visualising Correlations with a Heatmap_en.vtt 21.7 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/027 Making Predictions (Part 1) MSE & R-Squared_en.vtt 21.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/023 Model Simplification & Baysian Information Criterion_en.vtt 20.7 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/014 Reshaping and Slicing N-Dimensional Arrays_en.vtt 20.4 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals_en.vtt 20.2 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/005 Analyse and Evaluate the Results_en.vtt 20.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/011 [Python] - Generator Functions & the yield Keyword_en.vtt 19.9 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/035 Sparse Matrix (Part 2) Data Munging with Nested Loops_en.vtt 19.9 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/021 Running Gradient Descent with a MSE Cost Function_en.vtt 19.7 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/002 Create a Full Matrix_en.vtt 19.6 kB
  • 12 - Serving a Tensorflow Model through a Website/002 Saving Tensorflow Models_en.vtt 19.5 kB
  • 12 - Serving a Tensorflow Model through a Website/004 Converting a Model to Tensorflow.js_en.vtt 19.2 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/020 Improving the Model by Transforming the Data_en.vtt 19.2 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/010 Understanding the Tensorflow Graph Nodes and Edges_en.vtt 19.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2)_en.vtt 18.9 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/008 TensorFlow Sessions and Batching Data_en.vtt 18.7 kB
  • 03 - Python Programming for Data Science and Machine Learning/010 [Python] - Functions - Part 2 Arguments & Parameters_en.vtt 18.6 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/012 Techniques to Style Scatter Plots_en.vtt 18.5 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/007 Working with Index Data, Pandas Series, and Dummy Variables_en.vtt 18.4 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays_en.vtt 18.3 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/005 Pre-processing Scaling Inputs and Creating a Validation Dataset_en.vtt 18.2 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/011 Understanding Partial Derivatives and How to use SymPy_en.vtt 18.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/006 Joint & Conditional Probability_en.vtt 17.7 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/006 Making Predictions using InceptionResNet_en.vtt 17.5 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/003 Costs and Disadvantages of Neural Networks_en.vtt 17.4 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/013 Prediction and Model Evaluation_en.vtt 17.2 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function_en.vtt 17.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/019 Tokenizing, Removing Stop Words and the Python Set Data Structure_en.vtt 17.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/004 Clean and Explore the Data (Part 2) Find Missing Values_en.vtt 16.7 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/003 Count the Tokens to Train the Naive Bayes Model_en.vtt 16.6 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/004 Exploring the CIFAR Data_en.vtt 16.5 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/025 Residual Analysis (Part 1) Predicted vs Actual Values_en.vtt 16.1 kB
  • 12 - Serving a Tensorflow Model through a Website/005 Introducing the Website Project and Tooling_en.vtt 16.1 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/013 [Python] - Loops and Performance Considerations_en.vtt 16.1 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/005 Understanding the Power Rule & Creating Charts with Subplots_en.vtt 16.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries_en.vtt 15.9 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/010 Calculating Correlations and the Problem posed by Multicollinearity_en.vtt 15.9 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/031 Create the Vocabulary for the Spam Classifier_en.vtt 15.8 kB
  • 12 - Serving a Tensorflow Model through a Website/015 Making a Prediction from a Digit drawn on the HTML Canvas_en.vtt 15.7 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2)_en.vtt 15.3 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/004 LaTeX Markdown and Generating Data with Numpy_en.vtt 15.2 kB
  • 03 - Python Programming for Data Science and Machine Learning/015 [Python] - Tips, Code Style and Naming Conventions_en.vtt 15.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/028 Styling the Word Cloud with a Mask_en.vtt 14.8 kB
  • 03 - Python Programming for Data Science and Machine Learning/005 [Python] - Variables and Types_en.vtt 14.8 kB
  • 03 - Python Programming for Data Science and Machine Learning/011 [Python] - Functions - Part 3 Results & Return Values_en.vtt 14.8 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/004 Preprocessing Image Data and How RGB Works_en.vtt 14.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/016 Data Visualisation (Part 1) Pie Charts_en.vtt 14.4 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset_en.vtt 14.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/025 [Python] - Logical Operators to Create Subsets and Indices_en.vtt 13.7 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18180296-08-Naive-Bayes-with-scikit-learn.ipynb.zip 13.6 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/007 Bayes Theorem_en.vtt 13.5 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/034 Sparse Matrix (Part 1) Split the Training and Testing Data_en.vtt 13.5 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals_en.vtt 13.2 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/030 Styling Word Clouds with Custom Fonts_en.vtt 13.2 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/024 How to Analyse and Plot Regression Residuals_en.vtt 13.2 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems_en.vtt 13.1 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/009 Reading Files (Part 2) Stream Objects and Email Structure_en.vtt 13.1 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics_en.vtt 13.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/005 Visualising Data (Part 1) Historams, Distributions & Outliers_en.vtt 12.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/002 Gathering Email Data and Working with Archives & Text Editors_en.vtt 12.6 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/002 Gather & Clean the Data_en.vtt 12.5 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/019 Understanding Nested Loops and Plotting the MSE Function (Part 1)_en.vtt 12.4 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/027 Creating your First Word Cloud_en.vtt 12.3 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/038 Checkpoint Understanding the Data_en.vtt 12.2 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/007 Coding Challenge Solution Using other Keras Models_en.vtt 12.1 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/024 Advanced Subsetting on DataFrames the apply() Function_en.vtt 12.1 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/018 Implementing a MSE Cost Function_en.vtt 12.0 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/017 Transposing and Reshaping Arrays_en.vtt 12.0 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset_en.vtt 11.8 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/007 False Positive vs False Negatives_en.vtt 11.7 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/012 Implementing Batch Gradient Descent with SymPy_en.vtt 11.5 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/002 Joint Conditional Probability (Part 1) Dot Product_en.vtt 11.3 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/016 Introduction to the Mean Squared Error (MSE)_en.vtt 11.3 kB
  • 12 - Serving a Tensorflow Model through a Website/011 Data Pre-Processing for Tensorflow.js_en.vtt 11.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/008 Understanding Descriptive Statistics the Mean vs the Median_en.vtt 10.9 kB
  • 03 - Python Programming for Data Science and Machine Learning/006 [Python] - Lists and Arrays_en.vtt 10.8 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/026 Word Clouds & How to install Additional Python Packages_en.vtt 10.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files_en.vtt 10.7 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/005 Importing Keras Models and the Tensorflow Graph_en.vtt 10.6 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/008 Reading Files (Part 1) Absolute Paths and Relative Paths_en.vtt 10.5 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/016 How to Shuffle and Split Training & Testing Data_en.vtt 10.2 kB
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/001 The Human Brain and the Inspiration for Artificial Neural Networks_en.vtt 10.2 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/001 Setting up the Notebook and Understanding Delimiters in a Dataset_en.vtt 10.0 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/021 Removing HTML tags with BeautifulSoup_en.vtt 10.0 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/011 Model Evaluation and the Confusion Matrix_en.vtt 9.8 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/003 Joint Conditional Probablity (Part 2) Priors_en.vtt 9.8 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/021 How to Interpret Coefficients using p-Values and Statistical Significance_en.vtt 9.7 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/004 The Intuition behind the Linear Regression Model_en.vtt 9.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/020 Word Stemming & Removing Punctuation_en.vtt 9.6 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/022 Visualising the Optimisation on a 3D Surface_en.vtt 9.6 kB
  • 03 - Python Programming for Data Science and Machine Learning/009 [Python] - Functions - Part 1 Defining and Calling Functions_en.vtt 9.4 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/004 Making Predictions Comparing Joint Probabilities_en.vtt 9.0 kB
  • 12 - Serving a Tensorflow Model through a Website/001 What you'll make_en.vtt 8.9 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/017 Running a Multivariable Regression_en.vtt 8.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/001 How to Translate a Business Problem into a Machine Learning Problem_en.vtt 8.7 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/009 The Precision Metric_en.vtt 8.6 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/017 Data Visualisation (Part 2) Donut Charts_en.vtt 8.5 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/005 Calculate the Token Probabilities and Save the Trained Model_en.vtt 8.5 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/003 Introduction to Cost Functions_en.vtt 8.4 kB
  • 12 - Serving a Tensorflow Model through a Website/017 Publish and Share your Website!_en.vtt 8.4 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/002 Getting the Data and Loading it into Numpy Arrays_en.vtt 8.4 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/005 What is a Tensor_en.vtt 8.4 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/014 Cleaning Data (Part 2) Working with a DataFrame Index_en.vtt 8.1 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/006 Visualising Data (Part 2) Seaborn and Probability Density Functions_en.vtt 8.0 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/015 Concatenating Numpy Arrays_en.vtt 8.0 kB
  • 03 - Python Programming for Data Science and Machine Learning/001 Windows Users - Install Anaconda_en.vtt 7.9 kB
  • 02 - Predict Movie Box Office Revenue with Linear Regression/001 Introduction to Linear Regression & Specifying the Problem_en.vtt 7.8 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/002 Gathering the Boston House Price Data_en.vtt 7.7 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/009 Introduction to Correlation Understanding Strength & Direction_en.vtt 7.5 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/018 Introduction to Natural Language Processing (NLP)_en.vtt 7.4 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/022 Creating a Function for Text Processing_en.vtt 7.4 kB
  • 03 - Python Programming for Data Science and Machine Learning/002 Mac Users - Install Anaconda_en.vtt 7.2 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/004 Sum the Tokens across the Spam and Ham Subsets_en.vtt 7.1 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/005 The Accuracy Metric_en.vtt 6.8 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/18187740-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.8 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/015 Understanding Multivariable Regression_en.vtt 6.7 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/033 Coding Challenge Find the Longest Email_en.vtt 6.7 kB
  • 12 - Serving a Tensorflow Model through a Website/008 Adding a Favicon_en.vtt 6.7 kB
  • 03 - Python Programming for Data Science and Machine Learning/003 Does LSD Make You Better at Maths_en.vtt 6.6 kB
  • 12 - Serving a Tensorflow Model through a Website/21028850-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6.5 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/002 How a Machine Learns_en.vtt 6.5 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/012 Create a Pandas DataFrame of Email Bodies_en.vtt 6.4 kB
  • 12 - Serving a Tensorflow Model through a Website/21028968-12-TF-SavedModel-Export-Completed.ipynb.zip 6.3 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/015 Saving a JSON File with Pandas_en.vtt 6.2 kB
  • 01 - Introduction to the Course/001 What is Machine Learning_en.vtt 6.2 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/002 Installing Tensorflow and Keras for Jupyter_en.vtt 6.0 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/18180042-07-Bayes-Classifier-Training.ipynb.zip 6.0 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/008 The Recall Metric_en.vtt 5.9 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/003 Data Exploration and Understanding the Structure of the Input Data_en.vtt 5.9 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/001 Defining the Problem_en.vtt 5.7 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/003 Gathering the CIFAR 10 Dataset_en.vtt 5.6 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier_en.vtt 5.5 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/032 Coding Challenge Check for Membership in a Collection_en.vtt 5.4 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/029 Solving the Hamlet Challenge_en.vtt 5.3 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/010 Extracting the Text in the Email Body_en.vtt 5.3 kB
  • 01 - Introduction to the Course/002 What is Data Science_en.vtt 5.2 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/005 Basic Probability_en.vtt 4.7 kB
  • 12 - Serving a Tensorflow Model through a Website/21028978-x-test0-ylabel7.txt 4.7 kB
  • 12 - Serving a Tensorflow Model through a Website/21028982-x-test1-ylabel2.txt 4.7 kB
  • 12 - Serving a Tensorflow Model through a Website/21028988-x-test2-ylabel1.txt 4.7 kB
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/006 Coding Challenge Prepare the Test Data_en.vtt 4.7 kB
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/001 Solving a Business Problem with Image Classification_en.vtt 4.6 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/010 The F-score or F1 Metric_en.vtt 4.6 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/003 How to Add the Lesson Resources to the Project_en.vtt 4.3 kB
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/037 Coding Challenge Solution Preparing the Test Data_en.vtt 4.0 kB
  • 13 - Next Steps/001 Where next.html 4.0 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/018 How to Calculate the Model Fit with R-Squared_en.vtt 3.9 kB
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/001 What's Coming Up_en.vtt 3.4 kB
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/001 Set up the Testing Notebook_en.vtt 3.4 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/019 Introduction to Model Evaluation_en.vtt 3.4 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/18905386-boston-valuation.py 3.1 kB
  • 05 - Predict House Prices with Multivariable Linear Regression/18179928-04-Valuation-Tool.ipynb.zip 3.0 kB
  • 11 - Use Tensorflow to Classify Handwritten Digits/001 What's coming up_en.vtt 2.4 kB
  • 01 - Introduction to the Course/004 Top Tips for Succeeding on this Course.html 2.1 kB
  • 03 - Python Programming for Data Science and Machine Learning/004 Download the 12 Rules to Learn to Code.html 1.1 kB
  • 01 - Introduction to the Course/005 Course Resources List.html 1.1 kB
  • 13 - Next Steps/003 Stay in Touch!.html 1.1 kB
  • 01 - Introduction to the Course/003 Download the Syllabus.html 994 Bytes
  • 02 - Predict Movie Box Office Revenue with Linear Regression/007 Join the Student Community.html 715 Bytes
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/008 Any Feedback on this Section.html 527 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/009 Any Feedback on this Section.html 526 Bytes
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/014 Any Feedback on this Section.html 521 Bytes
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/024 Any Feedback on this Section.html 520 Bytes
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/040 Any Feedback on this Section.html 519 Bytes
  • 03 - Python Programming for Data Science and Machine Learning/017 Any Feedback on this Section.html 513 Bytes
  • 02 - Predict Movie Box Office Revenue with Linear Regression/008 Any Feedback on this Section.html 512 Bytes
  • 05 - Predict House Prices with Multivariable Linear Regression/033 Any Feedback on this Section.html 512 Bytes
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/013 Any Feedback on this Section.html 509 Bytes
  • 12 - Serving a Tensorflow Model through a Website/018 Any Feedback on this Section.html 500 Bytes
  • 11 - Use Tensorflow to Classify Handwritten Digits/015 Any Feedback on this Section.html 499 Bytes
  • 05 - Predict House Prices with Multivariable Linear Regression/013 A Note for the Next Lesson.html 476 Bytes
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/023 A Note for the Next Lesson.html 476 Bytes
  • 13 - Next Steps/002 What Modules Do You Want to See.html 431 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/008 Download the Complete Notebook Here.html 264 Bytes
  • 02 - Predict Movie Box Office Revenue with Linear Regression/006 Download the Complete Notebook Here.html 242 Bytes
  • 03 - Python Programming for Data Science and Machine Learning/016 Download the Complete Notebook Here.html 242 Bytes
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/023 Download the Complete Notebook Here.html 242 Bytes
  • 05 - Predict House Prices with Multivariable Linear Regression/032 Download the Complete Notebook Here.html 242 Bytes
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/039 Download the Complete Notebook Here.html 242 Bytes
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/007 Download the Complete Notebook Here.html 242 Bytes
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/012 Download the Complete Notebook Here.html 242 Bytes
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/013 Download the Complete Notebook Here.html 242 Bytes
  • 11 - Use Tensorflow to Classify Handwritten Digits/014 Download the Complete Notebook Here.html 242 Bytes
  • 02 - Predict Movie Box Office Revenue with Linear Regression/external-assets-links.txt 212 Bytes
  • 03 - Python Programming for Data Science and Machine Learning/18877814-lsd-math-score-data.csv 155 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 01 - Introduction to the Course/external-assets-links.txt 120 Bytes
  • 03 - Python Programming for Data Science and Machine Learning/external-assets-links.txt 83 Bytes
  • 04 - Introduction to Optimisation and the Gradient Descent Algorithm/external-assets-links.txt 83 Bytes
  • 05 - Predict House Prices with Multivariable Linear Regression/external-assets-links.txt 83 Bytes
  • 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/external-assets-links.txt 83 Bytes
  • 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/external-assets-links.txt 83 Bytes
  • 08 - Test and Evaluate a Naive Bayes Classifier Part 3/external-assets-links.txt 83 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/external-assets-links.txt 83 Bytes
  • 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/external-assets-links.txt 83 Bytes
  • 11 - Use Tensorflow to Classify Handwritten Digits/external-assets-links.txt 83 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/0. Websites you may like/[GigaCourse.Com].url 49 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！