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[GigaCourse.Com] Udemy - Machine Learning, Data Science and Generative AI with Python

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[GigaCourse.Com] Udemy - Machine Learning, Data Science and Generative AI with Python

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文件列表

  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!.mp4 334.5 MB
  • 14 - Retrieval Augmented Generation (RAG)/002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.mp4 193.4 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.mp4 179.0 MB
  • 11 - Generative Models/002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.mp4 156.1 MB
  • 08 - Apache Spark Machine Learning on Big Data/003 [Activity] Installing Spark.mp4 148.2 MB
  • 08 - Apache Spark Machine Learning on Big Data/007 Introduction to Decision Trees in Spark.mp4 140.5 MB
  • 11 - Generative Models/005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.mp4 132.2 MB
  • 06 - More Data Mining and Machine Learning Techniques/006 Reinforcement Learning.mp4 131.3 MB
  • 05 - Recommender Systems/005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.mp4 130.1 MB
  • 10 - Deep Learning and Neural Networks/017 The Ethics of Deep Learning.mp4 126.4 MB
  • 08 - Apache Spark Machine Learning on Big Data/008 [Activity] K-Means Clustering in Spark.mp4 121.8 MB
  • 10 - Deep Learning and Neural Networks/014 [Activity] Transfer Learning.mp4 116.4 MB
  • 10 - Deep Learning and Neural Networks/006 [Activity] Using Tensorflow, Part 1.mp4 112.9 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/004 [Activity] Variation and Standard Deviation.mp4 108.4 MB
  • 01 - Getting Started/005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 106.9 MB
  • 01 - Getting Started/006 [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 100.9 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/009 [Activity] Advanced Visualization with Seaborn.mp4 100.8 MB
  • 10 - Deep Learning and Neural Networks/007 [Activity] Using Tensorflow, Part 2.mp4 99.7 MB
  • 03 - Predictive Models/003 [Activity] Multiple Regression, and Predicting Car Prices.mp4 98.7 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/011 [Exercise] Conditional Probability.mp4 98.5 MB
  • 03 - Predictive Models/001 [Activity] Linear Regression.mp4 97.5 MB
  • 14 - Retrieval Augmented Generation (RAG)/001 Retrieval Augmented Generation (RAG) How it works, with some examples.mp4 97.4 MB
  • 09 - Experimental Design ML in the Real World/006 AB Test Gotchas.mp4 96.2 MB
  • 10 - Deep Learning and Neural Networks/009 [Activity] Using Keras to Predict Political Affiliations.mp4 93.2 MB
  • 11 - Generative Models/004 Generative Adversarial Networks (GAN's) - Playing with some demos.mp4 90.3 MB
  • 06 - More Data Mining and Machine Learning Techniques/002 [Activity] Using KNN to predict a rating for a movie.mp4 89.7 MB
  • 01 - Getting Started/007 [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 89.7 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/011 [Activity] Fine Tuning GPT with the IMDb dataset.mp4 89.3 MB
  • 08 - Apache Spark Machine Learning on Big Data/010 [Activity] Searching Wikipedia with Spark.mp4 88.1 MB
  • 05 - Recommender Systems/003 [Activity] Finding Movie Similarities using Cosine Similarity.mp4 86.7 MB
  • 05 - Recommender Systems/001 User-Based Collaborative Filtering.mp4 85.7 MB
  • 04 - Machine Learning with Python/011 Decision Trees Concepts.mp4 85.5 MB
  • 04 - Machine Learning with Python/004 [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 85.3 MB
  • 04 - Machine Learning with Python/014 [Activity] XGBoost.mp4 83.1 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/007 [Activity] Tokenization with Google CoLab and HuggingFace.mp4 82.8 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/008 [Activity] A Crash Course in matplotlib.mp4 82.5 MB
  • 10 - Deep Learning and Neural Networks/013 [Activity] Using a RNN for sentiment analysis.mp4 77.1 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/001 Types of Data (Numerical, Categorical, Ordinal).mp4 76.7 MB
  • 07 - Dealing with Real-World Data/003 Data Cleaning and Normalization.mp4 76.6 MB
  • 10 - Deep Learning and Neural Networks/008 [Activity] Introducing Keras.mp4 75.5 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/001 [Activity] The OpenAI Chat Completions API.mp4 73.9 MB
  • 10 - Deep Learning and Neural Networks/001 Deep Learning Pre-Requisites.mp4 73.8 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/010 [Activity] Covariance and Correlation.mp4 72.9 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace.mp4 72.7 MB
  • 10 - Deep Learning and Neural Networks/002 The History of Artificial Neural Networks.mp4 72.2 MB
  • 06 - More Data Mining and Machine Learning Techniques/004 [Activity] PCA Example with the Iris data set.mp4 69.0 MB
  • 08 - Apache Spark Machine Learning on Big Data/009 TF IDF.mp4 68.9 MB
  • 08 - Apache Spark Machine Learning on Big Data/011 [Activity] Using the Spark DataFrame API for MLLib.mp4 68.3 MB
  • 15 - Final Project/002 Final project review.mp4 67.6 MB
  • 06 - More Data Mining and Machine Learning Techniques/007 [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 65.8 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API.mp4 64.2 MB
  • 03 - Predictive Models/002 [Activity] Polynomial Regression.mp4 63.5 MB
  • 01 - Getting Started/001 Introduction.mp4 62.5 MB
  • 10 - Deep Learning and Neural Networks/010 Convolutional Neural Networks (CNN's).mp4 61.6 MB
  • 06 - More Data Mining and Machine Learning Techniques/005 Data Warehousing Overview ETL and ELT.mp4 61.6 MB
  • 04 - Machine Learning with Python/012 [Activity] Decision Trees Predicting Hiring Decisions.mp4 60.6 MB
  • 07 - Dealing with Real-World Data/002 [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 59.7 MB
  • 04 - Machine Learning with Python/001 Supervised vs. Unsupervised Learning, and TrainTest.mp4 59.4 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/013 Bayes' Theorem.mp4 58.8 MB
  • 05 - Recommender Systems/004 [Activity] Improving the Results of Movie Similarities.mp4 58.8 MB
  • 10 - Deep Learning and Neural Networks/003 [Activity] Deep Learning in the Tensorflow Playground.mp4 58.4 MB
  • 10 - Deep Learning and Neural Networks/011 [Activity] Using CNN's for handwriting recognition.mp4 55.4 MB
  • 15 - Final Project/001 Your final project assignment Mammogram Classification.mp4 54.1 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients.mp4 53.6 MB
  • 09 - Experimental Design ML in the Real World/004 [Activity] Hands-on With T-Tests.mp4 50.1 MB
  • 10 - Deep Learning and Neural Networks/005 Introducing Tensorflow.mp4 48.9 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/003 [Activity] Using mean, median, and mode in Python.mp4 46.7 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/001 The Transformer Architecture (encoders, decoders, and self-attention.).mp4 46.3 MB
  • 01 - Getting Started/012 Introducing the Pandas Library [Optional].mp4 46.3 MB
  • 11 - Generative Models/001 Variational Auto-Encoders (VAE's) - how they work.mp4 45.0 MB
  • 07 - Dealing with Real-World Data/010 Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 44.8 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/007 [Activity] Percentiles and Moments.mp4 44.6 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth.mp4 43.5 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT.mp4 41.7 MB
  • 04 - Machine Learning with Python/016 [Activity] Using SVM to cluster people using scikit-learn.mp4 40.4 MB
  • 06 - More Data Mining and Machine Learning Techniques/003 Dimensionality Reduction; Principal Component Analysis (PCA).mp4 40.0 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation.mp4 39.6 MB
  • 04 - Machine Learning with Python/013 Ensemble Learning.mp4 38.8 MB
  • 16 - You made it!/001 More to Explore.mp4 35.6 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/004 [Activity] The Embeddings API in OpenAI Finding similarities between words.mp4 34.5 MB
  • 10 - Deep Learning and Neural Networks/012 Recurrent Neural Networks (RNN's).mp4 34.4 MB
  • 09 - Experimental Design ML in the Real World/002 AB Testing Concepts.mp4 33.6 MB
  • 07 - Dealing with Real-World Data/004 [Activity] Cleaning web log data.mp4 32.5 MB
  • 10 - Deep Learning and Neural Networks/004 Deep Learning Details.mp4 32.4 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/004 How GPT Works, Part 1 The GPT Transformer Architecture.mp4 31.7 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/003 [Activity] The Images (DALL-E) API in OpenAI.mp4 31.0 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/005 The Legacy Fine-Tuning API for GPT Models in OpenAI.mp4 30.9 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/009 [Activity] The OpenAI Audio API (speech to text).mp4 30.1 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding.mp4 29.9 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/006 Common Data Distributions (Normal, Binomial, Poisson, etc).mp4 29.6 MB
  • 05 - Recommender Systems/006 [Exercise] Improve the recommender's results.mp4 29.4 MB
  • 03 - Predictive Models/004 Multi-Level Models.mp4 28.5 MB
  • 07 - Dealing with Real-World Data/006 [Activity] Detecting outliers.mp4 28.5 MB
  • 01 - Getting Started/008 Python Basics, Part 1 [Optional].mp4 28.2 MB
  • 04 - Machine Learning with Python/005 K-Means Clustering.mp4 27.3 MB
  • 08 - Apache Spark Machine Learning on Big Data/004 Spark Introduction.mp4 26.2 MB
  • 07 - Dealing with Real-World Data/001 BiasVariance Tradeoff.mp4 24.8 MB
  • 05 - Recommender Systems/002 Item-Based Collaborative Filtering.mp4 24.3 MB
  • 08 - Apache Spark Machine Learning on Big Data/005 Spark and the Resilient Distributed Dataset (RDD).mp4 23.4 MB
  • 04 - Machine Learning with Python/006 [Activity] Clustering people based on income and age.mp4 23.1 MB
  • 04 - Machine Learning with Python/002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 22.7 MB
  • 01 - Getting Started/009 [Activity] Python Basics, Part 2 [Optional].mp4 21.6 MB
  • 11 - Generative Models/006 Learning More about Deep Learning.mp4 21.2 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/003 Applications of Transformers (GPT).mp4 21.2 MB
  • 10 - Deep Learning and Neural Networks/016 Deep Learning Regularization with Dropout and Early Stopping.mp4 20.8 MB
  • 07 - Dealing with Real-World Data/008 Imputation Techniques for Missing Data.mp4 19.1 MB
  • 07 - Dealing with Real-World Data/009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 18.3 MB
  • 01 - Getting Started/002 Udemy 101 Getting the Most From This Course.mp4 18.2 MB
  • 09 - Experimental Design ML in the Real World/001 Deploying Models to Real-Time Systems.mp4 18.1 MB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/008 [Activity] The OpenAI Moderation API.mp4 18.0 MB
  • 04 - Machine Learning with Python/015 Support Vector Machines (SVM) Overview.mp4 17.1 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/008 [Activity] Positional Encoding.mp4 16.7 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/002 Mean, Median, Mode.mp4 16.7 MB
  • 11 - Generative Models/003 Generative Adversarial Networks (GAN's) - How they work.mp4 16.0 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/012 Exercise Solution Conditional Probability of Purchase by Age.mp4 15.7 MB
  • 08 - Apache Spark Machine Learning on Big Data/006 Introducing MLLib.mp4 15.4 MB
  • 07 - Dealing with Real-World Data/007 Feature Engineering and the Curse of Dimensionality.mp4 15.3 MB
  • 09 - Experimental Design ML in the Real World/003 T-Tests and P-Values.mp4 14.8 MB
  • 06 - More Data Mining and Machine Learning Techniques/001 K-Nearest-Neighbors Concepts.mp4 14.7 MB
  • 04 - Machine Learning with Python/007 Measuring Entropy.mp4 12.7 MB
  • 06 - More Data Mining and Machine Learning Techniques/009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 12.2 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/006 Fine Tuning Transfer Learning with Transformers.mp4 12.1 MB
  • 07 - Dealing with Real-World Data/005 Normalizing numerical data.mp4 10.8 MB
  • 04 - Machine Learning with Python/003 Bayesian Methods Concepts.mp4 10.3 MB
  • 09 - Experimental Design ML in the Real World/005 Determining How Long to Run an Experiment.mp4 10.2 MB
  • 04 - Machine Learning with Python/009 [Activity] MAC Installing Graphviz.mp4 9.5 MB
  • 10 - Deep Learning and Neural Networks/015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 8.9 MB
  • 01 - Getting Started/011 [Activity] Python Basics, Part 4 [Optional].mp4 8.6 MB
  • 06 - More Data Mining and Machine Learning Techniques/008 Understanding a Confusion Matrix.mp4 7.7 MB
  • 02 - Statistics and Probability Refresher, and Python Practice/005 Probability Density Function; Probability Mass Function.mp4 7.3 MB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/007 Transformers-MLCourse.ipynb 7.0 MB
  • 01 - Getting Started/010 [Activity] Python Basics, Part 3 [Optional].mp4 5.4 MB
  • 11 - Generative Models/005 GAN-on-Fashion-MNIST.ipynb 3.9 MB
  • 04 - Machine Learning with Python/010 [Activity] LINUX Installing Graphviz.mp4 2.6 MB
  • 11 - Generative Models/002 VariationalAutoEncoders.ipynb 1.4 MB
  • 04 - Machine Learning with Python/008 [Activity] WINDOWS Installing Graphviz.mp4 972.1 kB
  • 14 - Retrieval Augmented Generation (RAG)/002 Data-RAG.ipynb 102.8 kB
  • 11 - Generative Models/002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST_en.srt 56.0 kB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!_en.srt 47.0 kB
  • 14 - Retrieval Augmented Generation (RAG)/002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek_en.srt 41.7 kB
  • 14 - Retrieval Augmented Generation (RAG)/001 Retrieval Augmented Generation (RAG) How it works, with some examples_en.srt 38.1 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/009 [Activity] Advanced Visualization with Seaborn_en.srt 36.6 kB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek_en.srt 36.1 kB
  • 03 - Predictive Models/003 [Activity] Multiple Regression, and Predicting Car Prices_en.srt 35.0 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/011 [Exercise] Conditional Probability_en.srt 34.9 kB
  • 04 - Machine Learning with Python/014 [Activity] XGBoost_en.srt 34.5 kB
  • 08 - Apache Spark Machine Learning on Big Data/007 Introduction to Decision Trees in Spark_en.srt 33.9 kB
  • 11 - Generative Models/005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST_en.srt 33.4 kB
  • 10 - Deep Learning and Neural Networks/008 [Activity] Introducing Keras_en.srt 29.3 kB
  • 10 - Deep Learning and Neural Networks/006 [Activity] Using Tensorflow, Part 1_en.srt 28.3 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/007 [Activity] Percentiles and Moments_en.srt 27.5 kB
  • 06 - More Data Mining and Machine Learning Techniques/007 [Activity] Reinforcement Learning & Q-Learning with Gym_en.srt 27.2 kB
  • 10 - Deep Learning and Neural Networks/005 Introducing Tensorflow_en.srt 27.2 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/008 [Activity] A Crash Course in matplotlib_en.srt 26.7 kB
  • 10 - Deep Learning and Neural Networks/001 Deep Learning Pre-Requisites_en.srt 26.7 kB
  • 10 - Deep Learning and Neural Networks/009 [Activity] Using Keras to Predict Political Affiliations_en.srt 26.0 kB
  • 06 - More Data Mining and Machine Learning Techniques/006 Reinforcement Learning_en.srt 25.9 kB
  • 10 - Deep Learning and Neural Networks/014 [Activity] Transfer Learning_en.srt 25.9 kB
  • 10 - Deep Learning and Neural Networks/017 The Ethics of Deep Learning_en.srt 25.5 kB
  • 10 - Deep Learning and Neural Networks/007 [Activity] Using Tensorflow, Part 2_en.srt 25.5 kB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/001 [Activity] The OpenAI Chat Completions API_en.srt 25.5 kB
  • 10 - Deep Learning and Neural Networks/010 Convolutional Neural Networks (CNN's)_en.srt 25.4 kB
  • 08 - Apache Spark Machine Learning on Big Data/005 Spark and the Resilient Distributed Dataset (RDD)_en.srt 24.8 kB
  • 10 - Deep Learning and Neural Networks/002 The History of Artificial Neural Networks_en.srt 24.7 kB
  • 06 - More Data Mining and Machine Learning Techniques/002 [Activity] Using KNN to predict a rating for a movie_en.srt 24.7 kB
  • 10 - Deep Learning and Neural Networks/003 [Activity] Deep Learning in the Tensorflow Playground_en.srt 24.5 kB
  • 03 - Predictive Models/001 [Activity] Linear Regression_en.srt 24.3 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/010 [Activity] Covariance and Correlation_en.srt 24.3 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/004 [Activity] Variation and Standard Deviation_en.srt 23.5 kB
  • 10 - Deep Learning and Neural Networks/012 Recurrent Neural Networks (RNN's)_en.srt 23.5 kB
  • 15 - Final Project/002 Final project review_en.srt 22.8 kB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/001 The Transformer Architecture (encoders, decoders, and self-attention.)_en.srt 22.8 kB
  • 01 - Getting Started/012 Introducing the Pandas Library [Optional]_en.srt 22.4 kB
  • 07 - Dealing with Real-World Data/004 [Activity] Cleaning web log data_en.srt 22.3 kB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth_en.srt 22.2 kB
  • 11 - Generative Models/004 Generative Adversarial Networks (GAN's) - Playing with some demos_en.srt 22.2 kB
  • 11 - Generative Models/001 Variational Auto-Encoders (VAE's) - how they work_en.srt 22.2 kB
  • 08 - Apache Spark Machine Learning on Big Data/003 [Activity] Installing Spark_en.srt 21.8 kB
  • 08 - Apache Spark Machine Learning on Big Data/008 [Activity] K-Means Clustering in Spark_en.srt 21.6 kB
  • 09 - Experimental Design ML in the Real World/006 AB Test Gotchas_en.srt 21.4 kB
  • 10 - Deep Learning and Neural Networks/004 Deep Learning Details_en.srt 21.4 kB
  • 10 - Deep Learning and Neural Networks/013 [Activity] Using a RNN for sentiment analysis_en.srt 21.2 kB
  • 01 - Getting Started/005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials_en.srt 21.2 kB
  • 07 - Dealing with Real-World Data/002 [Activity] K-Fold Cross-Validation to avoid overfitting_en.srt 21.1 kB
  • 05 - Recommender Systems/005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering_en.srt 20.7 kB
  • 04 - Machine Learning with Python/012 [Activity] Decision Trees Predicting Hiring Decisions_en.srt 20.6 kB
  • 04 - Machine Learning with Python/016 [Activity] Using SVM to cluster people using scikit-learn_en.srt 20.5 kB
  • 04 - Machine Learning with Python/001 Supervised vs. Unsupervised Learning, and TrainTest_en.srt 19.9 kB
  • 02 - Statistics and Probability Refresher, and Python Practice/003 [Activity] Using mean, median, and mode in Python_en.srt 19.8 kB
  • 08 - Apache Spark Machine Learning on Big Data/004 Spark Introduction_en.srt 19.6 kB
  • 13 - The OpenAI API (Developing with GPT and ChatGPT)/002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API_en.srt 19.5 kB
  • 09 - Experimental Design ML in the Real World/001 Deploying Models to Real-Time Systems_en.srt 19.2 kB
  • 09 - Experimental Design ML in the Real World/002 AB Testing Concepts_en.srt 19.1 kB
  • 04 - Machine Learning with Python/011 Decision Trees Concepts_en.srt 19.1 kB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/007 [Activity] Tokenization with Google CoLab and HuggingFace_en.srt 19.1 kB
  • 06 - More Data Mining and Machine Learning Techniques/005 Data Warehousing Overview ETL and ELT_en.srt 18.5 kB
  • 01 - Getting Started/007 [Activity] LINUX Installing and Using Anaconda & Course Materials_en.srt 18.4 kB
  • 06 - More Data Mining and Machine Learning Techniques/004 [Activity] PCA Example with the Iris data set_en.srt 18.4 kB
  • 05 - Recommender Systems/003 [Activity] Finding Movie Similarities using Cosine Similarity_en.srt 18.3 kB
  • 05 - Recommender Systems/002 Item-Based Collaborative Filtering_en.srt 18.2 kB
  • 05 - Recommender Systems/001 User-Based Collaborative Filtering_en.srt 17.8 kB
  • 07 - Dealing with Real-World Data/008 Imputation Techniques for Missing Data_en.srt 17.7 kB
  • 07 - Dealing with Real-World Data/010 Binning, Transforming, Encoding, Scaling, and Shuffling_en.srt 17.3 kB
  • 01 - Getting Started/006 [Activity] MAC Installing and Using Anaconda & Course Materials_en.srt 17.3 kB
  • 10 - Deep Learning and Neural Networks/011 [Activity] Using CNN's for handwriting recognition_en.srt 17.2 kB
  • 04 - Machine Learning with Python/004 [Activity] Implementing a Spam Classifier with Naive Bayes_en.srt 17.0 kB
  • 05 - Recommender Systems/004 [Activity] Improving the Results of Movie Similarities_en.srt 16.6 kB
  • 07 - Dealing with Real-World Data/003 Data Cleaning and Normalization_en.srt 16.6 kB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/004 How GPT Works, Part 1 The GPT Transformer Architecture_en.srt 16.4 kB
  • 11 - Generative Models/003 Generative Adversarial Networks (GAN's) - How they work_en.srt 16.3 kB
  • 12 - Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients_en.srt 16.3 kB
  • 03 - Predictive Models/002 [Activity] Polynomial Regression_en.srt 16.1 kB
  • 04 - Machine Learning with Python/005 K-Means Clustering_en.srt 16.0 kB
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