CBTNuggets - Introduction to Machine Learning 2024-3

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CBTNuggets - Introduction to Machine Learning 2024-3

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收录时间：2024-11-24
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文件列表

  • 55. Design Effective Prompts for Large Language Models/2. Iterative Prompt Engineering.mp4 216.9 MB
  • 11. Examine Cost Functions and Parameter Tuning/6. Calculate Your Model's Performance.mp4 207.5 MB
  • 52. Explore Multi-Label Classification with TensorFlow/2. Binary, Multi-Class, and Multi-Label Classification.mp4 205.3 MB
  • 10. Apply Regression Concepts for Supervised Learning/3. Explore Linear Relationships Ordinary Least Squares.mp4 198.9 MB
  • 3. Define What is Machine Learning/1. Introduction.mp4 194.3 MB
  • 7. Define What is Machine Learning/1. Introduction.mp4 194.3 MB
  • 21. Build a K-Nearest Neighbors Classifier/1. Introduction.mp4 187.1 MB
  • 56. Implement LangChain in Language Model Workflows/3. Leverage LangChain Templating for Complex Prompts.mp4 186.7 MB
  • 55. Design Effective Prompts for Large Language Models/5. Challenge Build The AutoBot ChatBot To Manage Orders.mp4 178.6 MB
  • 9. Explore Data Pipelines and Linear Regression/5. Predicting Lumber Prices Feature Extraction.mp4 177.9 MB
  • 4. Setup a Machine Learning Development Environment/2. Anaconda, Conda and Jupyter - Locally.mp4 172.7 MB
  • 8. Setup a Machine Learning Development Environment/2. Locally.mp4 172.7 MB
  • 1. Explore How AI Agents Navigate Driving Directions/2. What is Artificial Intelligence.mp4 171.0 MB
  • 5. Explore How AI Agents Navigate Driving Directions/2. What is Artificial Intelligence.mp4 171.0 MB
  • 28. Explore Gradient Descent & Back Propagation/6. Split The Train Test Datasets.mp4 170.2 MB
  • 3. Define What is Machine Learning/2. What is Machine Learning.mp4 168.4 MB
  • 7. Define What is Machine Learning/2. What is Machine Learning.mp4 168.4 MB
  • 16. Implement Logistic Regression with Python/5. Implement Logistic Regression Part 1 Data Preprocessing, Cleaning, and Encoding .mp4 168.1 MB
  • 62. Explore Transformer Encoders and Decoders/3. Attention Is All You Need (Optional).mp4 165.4 MB
  • 17. Build a Python Decision Tree Classification Model/4. Introduction.mp4 163.3 MB
  • 3. Define What is Machine Learning/3. Supervised.mp4 162.5 MB
  • 7. Define What is Machine Learning/3. Supervised.mp4 162.5 MB
  • 20. Build a Support Vector Machine Classifier/4. Data Loading and PreProcessing.mp4 158.7 MB
  • 16. Implement Logistic Regression with Python/1. Introduction.mp4 158.1 MB
  • 63. Examine the Fundamentals of HuggingFace/5. Spaces.mp4 154.2 MB
  • 4. Setup a Machine Learning Development Environment/5. Cloud Services AWS, GCP, and Azure.mp4 153.3 MB
  • 8. Setup a Machine Learning Development Environment/5. Cloud Services AWS, GCP, and Azure.mp4 153.3 MB
  • 4. Setup a Machine Learning Development Environment/4. Google Colab.mp4 150.9 MB
  • 8. Setup a Machine Learning Development Environment/4. Google Colab.mp4 150.9 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/7. Challenge Implement LangChain Memory.mp4 150.4 MB
  • 3. Define What is Machine Learning/5. Build an Image Classifier.mp4 149.5 MB
  • 7. Define What is Machine Learning/5. Build an Image Classifier.mp4 149.5 MB
  • 23. Implement a Perceptron for Classification/4. Implement a Perceptron from Scratch.mp4 148.8 MB
  • 1. Explore How AI Agents Navigate Driving Directions/3. Grand Search Auto.mp4 147.3 MB
  • 5. Explore How AI Agents Navigate Driving Directions/3. Grand Search Auto.mp4 147.3 MB
  • 63. Examine the Fundamentals of HuggingFace/3. Models.mp4 140.3 MB
  • 55. Design Effective Prompts for Large Language Models/3. Build a Summarizer for Interesting Topics.mp4 140.3 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/6. The Power of Chaining LangChain Components.mp4 138.9 MB
  • 17. Build a Python Decision Tree Classification Model/2. Introduction.mp4 138.6 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/3. Route Queries Using Classification for Different Cases.mp4 137.5 MB
  • 58. Combine LangChain Components for Coherent Apps/6. RouterChain.mp4 137.2 MB
  • 61. Use LangChain to Chat with PDFs and Documents/7. Challenge.mp4 136.6 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/7. Challenge Filter Inputs with a Chain of Thought Prompt Filter.mp4 136.4 MB
  • 3. Define What is Machine Learning/6. Predicting Lumber Prices with Linear Regression.mp4 134.4 MB
  • 7. Define What is Machine Learning/6. Predicting Lumber Prices with Linear Regression.mp4 134.4 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/2. ConversationBufferMemory.mp4 132.3 MB
  • 50. Explore Multi-Class Classification with TensorFlow/2. Create a Teachable Machine Multi-Class Classifier.mp4 131.1 MB
  • 12. Implement Gradient Descent for Linear Regression/5. Implementing The Gradient Descent Algorithm.mp4 129.2 MB
  • 10. Apply Regression Concepts for Supervised Learning/5. Ordinary Least Squares with Matlab's PolyFit.mp4 128.7 MB
  • 17. Build a Python Decision Tree Classification Model/5. Introduction.mp4 127.0 MB
  • 9. Explore Data Pipelines and Linear Regression/2. What is a Machine Learning Model.mp4 125.9 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/5. Implement The OpenAI Moderation API.mp4 123.2 MB
  • 43. Evaluate Regression Models with TensorFlow/5. Challenge Solution.mp4 120.1 MB
  • 63. Examine the Fundamentals of HuggingFace/7. Challenge.mp4 118.4 MB
  • 22. Explore Neural Network Basics With The Perceptron/6. Build A Simple Binary Perceptron Classifier.mp4 117.4 MB
  • 23. Implement a Perceptron for Classification/3. The Perceptron Rule and Neurons.mp4 117.3 MB
  • 28. Explore Gradient Descent & Back Propagation/1. Introduction.mp4 116.2 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/4. One-Hot Encode Features and Build Model.mp4 114.8 MB
  • 42. Build a Simple Regression Model with TensorFlow/3. Build Model From Scratch.mp4 113.9 MB
  • 63. Examine the Fundamentals of HuggingFace/1. Introduction.mp4 113.8 MB
  • 41. Explore Neural Network Regression with TensorFlow/3. Neural Network Architecture.mp4 113.5 MB
  • 42. Build a Simple Regression Model with TensorFlow/6. Solution Part 1.mp4 113.2 MB
  • 28. Explore Gradient Descent & Back Propagation/7. Build a Linear Regression Model.mp4 111.9 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/2. Reshape, View, and Stack Tensors.mp4 111.0 MB
  • 33. Explore Multi-class Classification with PyTorch/2. Review of Binary Classification with PyTorch.mp4 111.0 MB
  • 15. Identify Key Classification Algorithms/1. Introduction.mp4 110.8 MB
  • 14. Explore Feature Engineering and Data Preparation/3. Handling Missing Data.mp4 109.9 MB
  • 18. Build a Python Random Forest Classification Model/4. Import Libraries, Feature Engineering and One-Hot Encoding.mp4 109.3 MB
  • 41. Explore Neural Network Regression with TensorFlow/4. Build a Model.mp4 109.1 MB
  • 2. Apply Probability to Real-World AI Problems/2. Probability of Rolling One 6-sided Die.mp4 109.0 MB
  • 6. Apply Probability to Real-World AI Problems/2. Probability of Rolling One 6-sided Die.mp4 109.0 MB
  • 4. Setup a Machine Learning Development Environment/1. Introduction.mp4 108.9 MB
  • 8. Setup a Machine Learning Development Environment/1. Introduction.mp4 108.9 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/4. Split Data for Train and Test Datasets.mp4 108.4 MB
  • 13. Vectorize Operations for Multiple Regression/5. Interpreting the Weights.mp4 106.2 MB
  • 14. Explore Feature Engineering and Data Preparation/1. Introduction.mp4 105.1 MB
  • 50. Explore Multi-Class Classification with TensorFlow/4. Load and Explore MNIST Fashion Dataset.mp4 104.6 MB
  • 1. Explore How AI Agents Navigate Driving Directions/6. Breadth-First Search.mp4 103.6 MB
  • 5. Explore How AI Agents Navigate Driving Directions/6. Breadth-First Search.mp4 103.6 MB
  • 53. Explore The Fundamentals of Large Language Models/2. What is a Large Language Model (LLM).mp4 103.4 MB
  • 49. Evaluate TensorFlow Classification Models/4. Adaptive Learning Rates part 3.mp4 102.7 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/7. Debugging with LangChain.mp4 102.6 MB
  • 60. Use LangChain to Interact with PDFs and Documents/6. Vector Stores.mp4 102.4 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/2. Review Matrix Multiplication Errors.mp4 101.9 MB
  • 56. Implement LangChain in Language Model Workflows/2. Compare Direct API Calls Vs. API Calls Through LangChain - LangChain API Call.mp4 101.3 MB
  • 46. Explore TensorFlow Neural Network Classification/2. What is Classification.mp4 101.2 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/6. Sanitize and Validate Inputs Injection Attacks.mp4 100.6 MB
  • 9. Explore Data Pipelines and Linear Regression/3. Predicting Lumber Prices Data Collection.mp4 100.2 MB
  • 13. Vectorize Operations for Multiple Regression/1. Introduction.mp4 99.5 MB
  • 41. Explore Neural Network Regression with TensorFlow/6. Solution Video.mp4 99.4 MB
  • 10. Apply Regression Concepts for Supervised Learning/1. Introduction.mp4 96.0 MB
  • 23. Implement a Perceptron for Classification/7. Bonus Resources.mp4 95.6 MB
  • 19. Apply Regularization to Overcome Overfitting/1. Introduction.mp4 94.6 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/5. Create Fourth Model.mp4 94.5 MB
  • 56. Implement LangChain in Language Model Workflows/6. Video Solution.mp4 93.5 MB
  • 13. Vectorize Operations for Multiple Regression/4. Non-Vectorized Operations.mp4 92.4 MB
  • 14. Explore Feature Engineering and Data Preparation/6. Define, Split and Scale Features.mp4 92.4 MB
  • 46. Explore TensorFlow Neural Network Classification/7. Challenge.mp4 91.0 MB
  • 17. Build a Python Decision Tree Classification Model/1. Introduction.mp4 90.0 MB
  • 15. Identify Key Classification Algorithms/2. From Regression to Classification.mp4 89.7 MB
  • 46. Explore TensorFlow Neural Network Classification/1. Introduction.mp4 89.6 MB
  • 12. Implement Gradient Descent for Linear Regression/4. Gradient Descent Behind the Scenes.mp4 89.6 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/1. Introduction.mp4 89.5 MB
  • 58. Combine LangChain Components for Coherent Apps/1. Introduction.mp4 89.5 MB
  • 30. Implement a Logistic Regression Model with PyTorch/7. Challenge Part 3 Bonus Self-Graded Take-Home Challenge.mp4 89.4 MB
  • 9. Explore Data Pipelines and Linear Regression/1. Introduction.mp4 88.9 MB
  • 4. Setup a Machine Learning Development Environment/6. Vast.ai the market leader in low-cost cloud GPU rental.mp4 88.3 MB
  • 8. Setup a Machine Learning Development Environment/6. Vast.ai the market leader in low-cost cloud GPU rental.mp4 88.3 MB
  • 23. Implement a Perceptron for Classification/1. Introduction.mp4 88.1 MB
  • 16. Implement Logistic Regression with Python/6. Implement Logistic Regression Part 2 Implement Logistic Regression and Measure Performance.mp4 87.4 MB
  • 62. Explore Transformer Encoders and Decoders/1. Introduction.mp4 86.2 MB
  • 10. Apply Regression Concepts for Supervised Learning/2. A Brief and Bizarre History of Linear Regression.mp4 86.2 MB
  • 16. Implement Logistic Regression with Python/4. Logistic Regression in 4 lines of Code.mp4 85.9 MB
  • 22. Explore Neural Network Basics With The Perceptron/1. Introduction.mp4 85.7 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/2. Web Chat Interfaces Vs. Programmatic Notebooks.mp4 85.4 MB
  • 21. Build a K-Nearest Neighbors Classifier/6. Data PreProcessing.mp4 85.0 MB
  • 21. Build a K-Nearest Neighbors Classifier/7. Build and Evaluate the Model.mp4 84.3 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/2. Review Neural Network Classification Without Non-Linearity.mp4 84.3 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/2. Review MNIST Fashion Multi-Class Classifier.mp4 83.3 MB
  • 58. Combine LangChain Components for Coherent Apps/7. Challenge.mp4 83.1 MB
  • 18. Build a Python Random Forest Classification Model/5. Train, Test, Predict, and Measure Model Performance.mp4 83.1 MB
  • 14. Explore Feature Engineering and Data Preparation/2. What is Feature Engineering.mp4 82.8 MB
  • 35. Discover What's New with PyTorch 2.0/1. Introduction.mp4 82.7 MB
  • 19. Apply Regularization to Overcome Overfitting/2. What is Overfitting.mp4 82.7 MB
  • 20. Build a Support Vector Machine Classifier/1. Introduction.mp4 82.3 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/3. Common Evaluation Metrics MAE, MSE, & Huber.mp4 81.9 MB
  • 61. Use LangChain to Chat with PDFs and Documents/3. Maximum Margin Relevance.mp4 80.9 MB
  • 42. Build a Simple Regression Model with TensorFlow/1. Introduction.mp4 80.8 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/6. Build a Neural Network Classification With Non-Linearity Step 4 Train Model .mp4 80.7 MB
  • 31. Explore Neural Network Classification with PyTorch/5. Train and Evaluate Model.mp4 80.7 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/5. ConversationSummaryBufferMemory.mp4 80.6 MB
  • 56. Implement LangChain in Language Model Workflows/4. Leverage Power of Templating for DRY Code.mp4 80.3 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/6. Challenge.mp4 79.7 MB
  • 22. Explore Neural Network Basics With The Perceptron/5. Why Linearly Separable Data Is Key.mp4 79.1 MB
  • 22. Explore Neural Network Basics With The Perceptron/8. Solution Video.mp4 79.1 MB
  • 19. Apply Regularization to Overcome Overfitting/3. Three Options for Handling Overfitting.mp4 78.7 MB
  • 28. Explore Gradient Descent & Back Propagation/4. Back Propagation.mp4 78.3 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/5. Explore Hyperparameter Tuning.mp4 78.1 MB
  • 4. Setup a Machine Learning Development Environment/3. Anaconda, Conda and Jupyter - Starting and Ending a Session .mp4 77.8 MB
  • 8. Setup a Machine Learning Development Environment/3. Starting and Ending a Session.mp4 77.8 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/1. Review Non-Linearly Separable Data.mp4 77.8 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/2. Squeezing Tensors.mp4 77.7 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/5. The Challenge.mp4 77.6 MB
  • 1. Explore How AI Agents Navigate Driving Directions/7. Breadth-First Search.mp4 77.5 MB
  • 5. Explore How AI Agents Navigate Driving Directions/7. Greedy-Best First and A Search.mp4 77.5 MB
  • 18. Build a Python Random Forest Classification Model/3. Random Forest Concepts.mp4 77.4 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/8. Challenge.mp4 77.2 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/1. Introduction.mp4 77.0 MB
  • 20. Build a Support Vector Machine Classifier/5. Build and Evaluate the Model.mp4 77.0 MB
  • 20. Build a Support Vector Machine Classifier/2. What is a Support Vector Machine.mp4 76.8 MB
  • 53. Explore The Fundamentals of Large Language Models/7. Challenge Connect Google Colab to ChatGPT via OpenAI's API.mp4 76.8 MB
  • 12. Implement Gradient Descent for Linear Regression/3. Exploring The Gradient Descent Algorithm.mp4 76.6 MB
  • 2. Apply Probability to Real-World AI Problems/5. Bayesian Networks.mp4 76.6 MB
  • 6. Apply Probability to Real-World AI Problems/5. Bayesian Networks.mp4 76.6 MB
  • 12. Implement Gradient Descent for Linear Regression/2. Exploring Gradient Descent Concepts.mp4 76.3 MB
  • 11. Examine Cost Functions and Parameter Tuning/1. Introduction.mp4 75.8 MB
  • 10. Apply Regression Concepts for Supervised Learning/6. Challenge.mp4 75.3 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/2. Generate Linear Transformation Data.mp4 75.3 MB
  • 25. Leverage PyTorch Tensor Attributes and Operators/5. The PyTorch Double Challenge.mp4 75.3 MB
  • 60. Use LangChain to Interact with PDFs and Documents/4. Document Separation.mp4 75.1 MB
  • 21. Build a K-Nearest Neighbors Classifier/2. What is K-Nearest Neighbors.mp4 75.1 MB
  • 23. Implement a Perceptron for Classification/6. Solution Video.mp4 75.0 MB
  • 35. Discover What's New with PyTorch 2.0/4. Traditional PyTorch 1.0 Vs PyTorch 2.0 torch.compile( ).mp4 74.8 MB
  • 63. Examine the Fundamentals of HuggingFace/4. Datasets.mp4 74.5 MB
  • 13. Vectorize Operations for Multiple Regression/2. Multiple Linear Regression.mp4 74.4 MB
  • 60. Use LangChain to Interact with PDFs and Documents/5. Embeddings.mp4 74.2 MB
  • 19. Apply Regularization to Overcome Overfitting/6. Perform Logistic Regression with Regularization.mp4 74.2 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/3. Create Second Model.mp4 74.2 MB
  • 14. Explore Feature Engineering and Data Preparation/4. Handling Outliers.mp4 74.0 MB
  • 58. Combine LangChain Components for Coherent Apps/3. LLMChain.mp4 74.0 MB
  • 43. Evaluate Regression Models with TensorFlow/3. Preprocess Data.mp4 73.8 MB
  • 2. Apply Probability to Real-World AI Problems/3. Probability of Rolling Two 6-sided Dice.mp4 73.8 MB
  • 6. Apply Probability to Real-World AI Problems/3. Probability of Rolling Two 6-sided Dice.mp4 73.8 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/6. Challenge.mp4 73.5 MB
  • 61. Use LangChain to Chat with PDFs and Documents/6. Chat Q&A Part 2.mp4 73.5 MB
  • 1. Explore How AI Agents Navigate Driving Directions/5. Depth-First Search.mp4 73.0 MB
  • 5. Explore How AI Agents Navigate Driving Directions/5. Depth-First Search.mp4 73.0 MB
  • 50. Explore Multi-Class Classification with TensorFlow/6. Solution Video.mp4 73.0 MB
  • 25. Leverage PyTorch Tensor Attributes and Operators/2. Tensor attributes.mp4 72.9 MB
  • 60. Use LangChain to Interact with PDFs and Documents/1. Introduction.mp4 72.9 MB
  • 18. Build a Python Random Forest Classification Model/1. Introduction.mp4 72.3 MB
  • 12. Implement Gradient Descent for Linear Regression/1. Introduction.mp4 72.3 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/3. Squeeze and Unsqueeze Tensors.mp4 72.0 MB
  • 15. Identify Key Classification Algorithms/5. Random Forests.mp4 71.8 MB
  • 19. Apply Regularization to Overcome Overfitting/5. Comparing Cost Functions.mp4 71.7 MB
  • 21. Build a K-Nearest Neighbors Classifier/3. KNN vs. Other Classifiers.mp4 71.5 MB
  • 35. Discover What's New with PyTorch 2.0/3. Key Features of PyTorch 2.0.mp4 71.3 MB
  • 22. Explore Neural Network Basics With The Perceptron/3. Perceptrons As Artificial Neurons.mp4 70.6 MB
  • 20. Build a Support Vector Machine Classifier/3. Optimal Hyperplanes and the Margin.mp4 70.5 MB
  • 42. Build a Simple Regression Model with TensorFlow/4. Challenge Improve Model.mp4 70.0 MB
  • 25. Leverage PyTorch Tensor Attributes and Operators/1. Introduction.mp4 70.0 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/1. Introduction.mp4 69.7 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/5. Mini-Challenge Model Training & Model Evaluation.mp4 69.7 MB
  • 10. Apply Regression Concepts for Supervised Learning/4. Seaborn Line of Best Fit.mp4 69.6 MB
  • 13. Vectorize Operations for Multiple Regression/3. Vectorization.mp4 69.1 MB
  • 47. Build a Neural Network Classifier with TensorFlow/5. Visualize and Evaluate Model.mp4 68.9 MB
  • 15. Identify Key Classification Algorithms/3. Logistic Regression.mp4 68.6 MB
  • 31. Explore Neural Network Classification with PyTorch/4. Define Neural Network Architecture.mp4 68.6 MB
  • 58. Combine LangChain Components for Coherent Apps/5. SequentialChain.mp4 68.5 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/3. Perform math calculation using an Math LLM.mp4 68.5 MB
  • 31. Explore Neural Network Classification with PyTorch/3. Load Make Moons Dataset & Pre-processing.mp4 68.0 MB
  • 55. Design Effective Prompts for Large Language Models/4. Implement Supervised Learning Through Inference.mp4 67.9 MB
  • 38. Implement Matrix Multiplication with TensorFlow/5. Perform Matrix Multiplication.mp4 67.9 MB
  • 49. Evaluate TensorFlow Classification Models/1. Review Learning Rates.mp4 67.5 MB
  • 16. Implement Logistic Regression with Python/2. What is Logistic Regression.mp4 67.5 MB
  • 43. Evaluate Regression Models with TensorFlow/1. Introduction.mp4 67.2 MB
  • 25. Leverage PyTorch Tensor Attributes and Operators/4. Matrix Multiplication.mp4 67.2 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/8. Solution Video.mp4 67.1 MB
  • 41. Explore Neural Network Regression with TensorFlow/2. What is Regression Analysis.mp4 67.0 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/7. Challenge Part 2.mp4 66.9 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/7. Solution Part 1.mp4 66.8 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/6. Saving and Loading PyTorch Models.mp4 66.8 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/2. What Is PyTorch and Why It Is Useful.mp4 66.7 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/7. Solution.mp4 66.6 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/8. Challenge.mp4 66.6 MB
  • 22. Explore Neural Network Basics With The Perceptron/7. Challenge Complete The Perceptron Function 🍩.mp4 66.5 MB
  • 17. Build a Python Decision Tree Classification Model/3. Introduction.mp4 66.3 MB
  • 46. Explore TensorFlow Neural Network Classification/6. Classification Code Example.mp4 65.7 MB
  • 36. Explore TensorFlow Machine Learning Foundations/6. Challenge.mp4 65.5 MB
  • 50. Explore Multi-Class Classification with TensorFlow/1. Compare Binary and Multi-Class Classification.mp4 65.2 MB
  • 11. Examine Cost Functions and Parameter Tuning/5. Cost Functions.mp4 65.1 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/4. Use Wikipedia to Find General Information.mp4 64.6 MB
  • 1. Explore How AI Agents Navigate Driving Directions/4. Explore the Frontier.mp4 64.6 MB
  • 5. Explore How AI Agents Navigate Driving Directions/4. Explore the Frontier.mp4 64.6 MB
  • 47. Build a Neural Network Classifier with TensorFlow/3. Create Circles Dataset & EDA.mp4 64.1 MB
  • 14. Explore Feature Engineering and Data Preparation/5. One Hot Encoding.mp4 64.0 MB
  • 61. Use LangChain to Chat with PDFs and Documents/5. Chat Q&A Part 1.mp4 63.7 MB
  • 46. Explore TensorFlow Neural Network Classification/5. What is Multi-Label Classification.mp4 63.5 MB
  • 19. Apply Regularization to Overcome Overfitting/4. Overfitting for Classification.mp4 63.3 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/3. ConversationBufferWindowMemory.mp4 63.3 MB
  • 11. Examine Cost Functions and Parameter Tuning/4. Root Mean Squared Error.mp4 62.9 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/3. Build a Neural Network Classification With Non-Linearity Step 1 Load Dataset, Pre-processing, and Make Circles.mp4 62.8 MB
  • 30. Implement a Logistic Regression Model with PyTorch/1. Introduction.mp4 62.8 MB
  • 56. Implement LangChain in Language Model Workflows/1. Introduction.mp4 62.6 MB
  • 3. Define What is Machine Learning/4. Unsupervised.mp4 62.5 MB
  • 7. Define What is Machine Learning/4. Unsupervised.mp4 62.5 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/5. Index Tensors.mp4 62.1 MB
  • 53. Explore The Fundamentals of Large Language Models/1. Introduction.mp4 62.0 MB
  • 42. Build a Simple Regression Model with TensorFlow/2. Build a Small Regression Model from Memory .mp4 62.0 MB
  • 42. Build a Simple Regression Model with TensorFlow/5. Solution Part 1.mp4 62.0 MB
  • 38. Implement Matrix Multiplication with TensorFlow/6. Challenge.mp4 61.6 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/6. Challenge Tensor Transformer.mp4 61.6 MB
  • 2. Apply Probability to Real-World AI Problems/4. Conditional Probability.mp4 61.6 MB
  • 6. Apply Probability to Real-World AI Problems/4. Conditional Probability.mp4 61.6 MB
  • 31. Explore Neural Network Classification with PyTorch/2. Review Logistic Regression PyTorch Workflow.mp4 61.6 MB
  • 31. Explore Neural Network Classification with PyTorch/1. Introduction.mp4 61.5 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/5. Leverage Tensors Programmatically.mp4 61.4 MB
  • 18. Build a Python Random Forest Classification Model/2. What is a Random Forest.mp4 61.1 MB
  • 41. Explore Neural Network Regression with TensorFlow/5. Challenge.mp4 61.1 MB
  • 38. Implement Matrix Multiplication with TensorFlow/4. Matrix Multiplication Foundations.mp4 61.1 MB
  • 61. Use LangChain to Chat with PDFs and Documents/4. ContextualCompressionRetriever + MMR.mp4 59.7 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/8. Challenge PyTorch Workflows.mp4 59.1 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/6. Make Predictions and Evaluate Model.mp4 59.1 MB
  • 15. Identify Key Classification Algorithms/4. Decision Trees.mp4 58.8 MB
  • 43. Evaluate Regression Models with TensorFlow/2. Regression Challenge.mp4 58.5 MB
  • 36. Explore TensorFlow Machine Learning Foundations/5. Create Random Tensors with Numpy.mp4 58.2 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/1. Introduction.mp4 58.2 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/3. Load and Visualize Dataset.mp4 57.9 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/2. Review Explore Multi-class Classification with PyTorch.mp4 57.4 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/3. Min, Max, Mean, and Sum (Tensor Aggregation).mp4 57.2 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/3. Create, Preprocess, and Visualize the Spiral Dataset.mp4 57.0 MB
  • 52. Explore Multi-Label Classification with TensorFlow/3. Start Building a Multi-Label Classifier.mp4 56.9 MB
  • 46. Explore TensorFlow Neural Network Classification/3. What is Binary Classification.mp4 56.8 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/4. Build a Neural Network Classification With Non-Linearity Step 2 Define Neural Network Architecture.mp4 56.6 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/8. Solution Video.mp4 56.6 MB
  • 28. Explore Gradient Descent & Back Propagation/3. Forward Propagation.mp4 56.6 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/5. Build a Neural Network Classification With Non-Linearity Step 3 Add Non-Linear Activation Function ReLu.mp4 56.4 MB
  • 62. Explore Transformer Encoders and Decoders/7. What is HuggingFace Again.mp4 56.1 MB
  • 9. Explore Data Pipelines and Linear Regression/4. Predicting Lumber Prices Data Cleaning & Preprocessing.mp4 56.1 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/7. Challenge.mp4 56.0 MB
  • 58. Combine LangChain Components for Coherent Apps/4. SimpleSequentialChain.mp4 55.9 MB
  • 33. Explore Multi-class Classification with PyTorch/3. Step 1 Setup and Prepare Data.mp4 55.6 MB
  • 22. Explore Neural Network Basics With The Perceptron/4. How Activation Functions Work.mp4 55.6 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/4. Numpy = Friend ❤️.mp4 55.4 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/1. Introduction.mp4 55.3 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/5. GPU & TPU Tensor Optimization.mp4 55.0 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/2. Leverage LangChain Agents.mp4 54.5 MB
  • 21. Build a K-Nearest Neighbors Classifier/4. What is Imbalanced Data.mp4 54.5 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/4. Leverage Tensors Concepts.mp4 54.5 MB
  • 61. Use LangChain to Chat with PDFs and Documents/2. Similarity Search.mp4 54.4 MB
  • 53. Explore The Fundamentals of Large Language Models/4. Two Kinds of LLMs Base and Instruction Tuned.mp4 54.4 MB
  • 52. Explore Multi-Label Classification with TensorFlow/5. Evaluate Model.mp4 54.1 MB
  • 15. Identify Key Classification Algorithms/7. Perceptrons.mp4 53.7 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/6. Solution Video.mp4 53.5 MB
  • 21. Build a K-Nearest Neighbors Classifier/5. Data Loading and EDA.mp4 53.4 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/5. Softmax and Validation Exploration.mp4 52.8 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/2. Review Matrix Multiplication.mp4 52.8 MB
  • 25. Leverage PyTorch Tensor Attributes and Operators/3. Tensor Math Operators.mp4 52.6 MB
  • 51. Tune Multi-Class Classification TensorFlow Models/7. Solution Video.mp4 52.4 MB
  • 43. Evaluate Regression Models with TensorFlow/4. Challenge Build Model.mp4 52.1 MB
  • 16. Implement Logistic Regression with Python/3. The Sigmoid Formula and Function.mp4 51.8 MB
  • 36. Explore TensorFlow Machine Learning Foundations/1. Introduction.mp4 51.0 MB
  • 55. Design Effective Prompts for Large Language Models/1. Introduction.mp4 50.7 MB
  • 36. Explore TensorFlow Machine Learning Foundations/2. Introduction to TensorFlow Tensors.mp4 50.2 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/5. Tensor Expansion.mp4 50.2 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/9. Solution Video.mp4 49.9 MB
  • 47. Build a Neural Network Classifier with TensorFlow/7. Solution Video.mp4 49.8 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/4. Permute Tensors.mp4 49.3 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/1. Introduction.mp4 49.0 MB
  • 60. Use LangChain to Interact with PDFs and Documents/2. Retrieval Augmented Generation (RAG) over 2 Skills.mp4 49.0 MB
  • 30. Implement a Logistic Regression Model with PyTorch/4. Part2 Build model.mp4 48.7 MB
  • 52. Explore Multi-Label Classification with TensorFlow/4. Build a Sequential Multi-Label Model.mp4 48.7 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/6. Challenge.mp4 48.6 MB
  • 60. Use LangChain to Interact with PDFs and Documents/3. Document Loaders.mp4 48.5 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/4. Create Third Model.mp4 48.1 MB
  • 30. Implement a Logistic Regression Model with PyTorch/3. Part1 Import Libraries, Define Model. and Load the data.mp4 47.9 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/7. Challenge.mp4 47.4 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/1. Introduction.mp4 47.4 MB
  • 63. Examine the Fundamentals of HuggingFace/2. What is HuggingFace 🤗.mp4 46.9 MB
  • 35. Discover What's New with PyTorch 2.0/5. Challenge .mp4 46.5 MB
  • 24. Explore PyTorch Fundamentals for Machine Learning/3. Set up a PyTorch Development Environment.mp4 46.5 MB
  • 33. Explore Multi-class Classification with PyTorch/7. Solution Videos Training Loop.mp4 46.2 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/1. Introduction.mp4 46.2 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/6. Explore Underfitting and Overfitting.mp4 46.1 MB
  • 15. Identify Key Classification Algorithms/6. Support Vector Machines.mp4 45.8 MB
  • 33. Explore Multi-class Classification with PyTorch/6. Challenge .mp4 45.5 MB
  • 20. Build a Support Vector Machine Classifier/6. Breast Cancer Wisconsin (Diagnostic) Dataset.mp4 44.7 MB
  • 58. Combine LangChain Components for Coherent Apps/2. Chaining in LangChain.mp4 44.7 MB
  • 47. Build a Neural Network Classifier with TensorFlow/1. Introduction.mp4 43.9 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/2. Device Agnostic Conditions & Load Data.mp4 43.8 MB
  • 28. Explore Gradient Descent & Back Propagation/5. Training, Validation, and Test Datasets.mp4 43.5 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/4. Navigating Positional Min Max Values.mp4 43.3 MB
  • 61. Use LangChain to Chat with PDFs and Documents/1. Introduction.mp4 43.3 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/2. Create Circles DataSet.mp4 43.2 MB
  • 31. Explore Neural Network Classification with PyTorch/7. Challenge PyTorch Workflow.mp4 42.7 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/4. Model Building.mp4 42.7 MB
  • 49. Evaluate TensorFlow Classification Models/2. Adaptive Learning Rates part 1.mp4 42.2 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/7. Solution Video.mp4 42.0 MB
  • 33. Explore Multi-class Classification with PyTorch/5. Step 3 Define Neural Network Architecture.mp4 41.9 MB
  • 23. Implement a Perceptron for Classification/5. The Perceptron Challenge.mp4 41.8 MB
  • 11. Examine Cost Functions and Parameter Tuning/2. Mean Absolute Error.mp4 41.5 MB
  • 47. Build a Neural Network Classifier with TensorFlow/8. Bonus Video.mp4 41.4 MB
  • 62. Explore Transformer Encoders and Decoders/2. What are Transformers.mp4 41.3 MB
  • 52. Explore Multi-Label Classification with TensorFlow/6. Challenge.mp4 41.1 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/1. Introduction.mp4 40.7 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/3. One-Hot Encoding.mp4 40.7 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/7. Challenge .mp4 40.5 MB
  • 33. Explore Multi-class Classification with PyTorch/4. Step 2 Visualize Data (EDA).mp4 40.2 MB
  • 46. Explore TensorFlow Neural Network Classification/4. What is Multi-Class Classification.mp4 40.2 MB
  • 33. Explore Multi-class Classification with PyTorch/8. Solution Videos Evaluation and Decision Boundary.mp4 39.8 MB
  • 53. Explore The Fundamentals of Large Language Models/5. System Messages and Tokens.mp4 39.6 MB
  • 62. Explore Transformer Encoders and Decoders/8. Solution Video.mp4 39.5 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/3. Altering Tensors.mp4 39.0 MB
  • 46. Explore TensorFlow Neural Network Classification/8. Solution.mp4 38.8 MB
  • 27. Apply PyTorch Tensor Manipulation and Indexing/1, Introduction.mp4 38.7 MB
  • 26. Explore Fundamental PyTorch Tensor Operations/7. Bonus Resources.mp4 38.6 MB
  • 13. Vectorize Operations for Multiple Regression/6. Vectorized Operations.mp4 38.5 MB
  • 30. Implement a Logistic Regression Model with PyTorch/2. Review Sklearn Titanic Classification.mp4 38.3 MB
  • 29. Predict Ice Cream Sales with PyTorch Regression/3. Pre-Processing.mp4 37.9 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/2. Handle Imports & Load Dataset.mp4 37.7 MB
  • 35. Discover What's New with PyTorch 2.0/2. Universal Device Setup in PyTorch 2.0.mp4 37.7 MB
  • 30. Implement a Logistic Regression Model with PyTorch/6. Challenge Part 1 Evaluate the Model .mp4 37.6 MB
  • 1. Explore How AI Agents Navigate Driving Directions/1. Introduction.mp4 37.4 MB
  • 5. Explore How AI Agents Navigate Driving Directions/1. Introduction.mp4 37.4 MB
  • 30. Implement a Logistic Regression Model with PyTorch/5. Part 3 Fit model.mp4 37.3 MB
  • 47. Build a Neural Network Classifier with TensorFlow/6. Challenge.mp4 37.3 MB
  • 23. Implement a Perceptron for Classification/2. What is a Perceptron.mp4 36.8 MB
  • 52. Explore Multi-Label Classification with TensorFlow/7. Solution Video.mp4 36.4 MB
  • 53. Explore The Fundamentals of Large Language Models/3. How do LLMs work.mp4 36.4 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/5. Define Model Architecture.mp4 36.3 MB
  • 47. Build a Neural Network Classifier with TensorFlow/4. Build, Compile, and Train Model.mp4 36.2 MB
  • 57. Implement LangChain Memory for Autonomous Tasks/4. ConversationTokenBufferMemory.mp4 36.0 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/1. Introduction.mp4 35.9 MB
  • 11. Examine Cost Functions and Parameter Tuning/3. Mean Squared Error.mp4 35.8 MB
  • 22. Explore Neural Network Basics With The Perceptron/2. Neurons as the building blocks of neural networks.mp4 35.6 MB
  • 44. Visualize and Evaluate Performance with TensorFlow/5. Define Basic Model Architecture.mp4 35.3 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/7. Tensor Positional Methods.mp4 35.0 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/6. Changing Tensor Data Types & Tensor Aggregation.mp4 34.2 MB
  • 14. Explore Feature Engineering and Data Preparation/7. Measuring Survival Accuracy .mp4 34.0 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/7. Build a Neural Network Classification With Non-Linearity Step 5 Evaluate Model.mp4 33.7 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/6. Create new custom agents and tooling (BabyAGI).mp4 33.1 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/3. One-hot Encode & Separate Features and Target.mp4 32.9 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/6. Evaluate Model and Visualize Loss.mp4 32.8 MB
  • 53. Explore The Fundamentals of Large Language Models/6. System Messages and Tokens Part 2.mp4 32.8 MB
  • 50. Explore Multi-Class Classification with TensorFlow/5. Challenge.mp4 32.4 MB
  • 49. Evaluate TensorFlow Classification Models/6. Solution Video.mp4 32.2 MB
  • 18. Build a Python Random Forest Classification Model/6. Bonus Hyperparameter Tuning Video.mp4 31.4 MB
  • 52. Explore Multi-Label Classification with TensorFlow/1. Introduction.mp4 31.4 MB
  • 2. Apply Probability to Real-World AI Problems/1. Introduction.mp4 31.3 MB
  • 6. Apply Probability to Real-World AI Problems/1. Introduction.mp4 31.3 MB
  • 62. Explore Transformer Encoders and Decoders/5. Decoders.mp4 31.0 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/9. Challenge 2.mp4 30.1 MB
  • 49. Evaluate TensorFlow Classification Models/5. Big Five Evaluation Metrics.mp4 29.7 MB
  • 49. Evaluate TensorFlow Classification Models/3. Adaptive Learning Rates part 2.mp4 29.5 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/4. Transpose & Reshape Tensors.mp4 29.4 MB
  • 38. Implement Matrix Multiplication with TensorFlow/3. TensorFlow Math Functions.mp4 28.1 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/2. Why Shuffle Tensors.mp4 28.1 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/1. Introduction.mp4 28.0 MB
  • 56. Implement LangChain in Language Model Workflows/5. Challenge.mp4 27.4 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/4. Define Neural Network Architecture.mp4 26.9 MB
  • 47. Build a Neural Network Classifier with TensorFlow/2. Pseudocode Image Classification.mp4 26.8 MB
  • 62. Explore Transformer Encoders and Decoders/4. Encoders.mp4 25.2 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/4. Perform TrainTest Split.mp4 25.2 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/8. Challenge .mp4 25.0 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/4. Tensor Attributes.mp4 24.5 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/8. Solution Part 2.mp4 24.1 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/3. TensorFlow Seeds.mp4 23.7 MB
  • 35. Discover What's New with PyTorch 2.0/6. Challenge 2.mp4 23.7 MB
  • 40. Squeeze, Encode, and Optimize TensorFlow Tensors/6. Challenge.mp4 23.6 MB
  • 32. Build a PyTorch Classifier with Non-Linearity/1. Introduction.mp4 23.1 MB
  • 54. Build LLM Apps with ChatGPT and the OpenAI API/4. Evaluate Inputs to Prevent Prompt Injections.mp4 22.6 MB
  • 36. Explore TensorFlow Machine Learning Foundations/3. Introduction to TensorFlow Tensors Part 2.mp4 22.4 MB
  • 59. Build Task-Driven Autonomous Agents with LangChain/5. Program using a Python REPL tool.mp4 22.3 MB
  • 2. Apply Probability to Real-World AI Problems/6. Recapitulation.mp4 21.7 MB
  • 6. Apply Probability to Real-World AI Problems/6. Recapitulation.mp4 21.7 MB
  • 50. Explore Multi-Class Classification with TensorFlow/3. Review Model Building Steps.mp4 21.5 MB
  • 36. Explore TensorFlow Machine Learning Foundations/4. Create Tensors with TensorFlow.mp4 20.9 MB
  • 38. Implement Matrix Multiplication with TensorFlow/1. Introduction.mp4 18.3 MB
  • 38. Implement Matrix Multiplication with TensorFlow/2. Basic Tensor Operation.mp4 17.7 MB
  • 62. Explore Transformer Encoders and Decoders/6. Encoder-Decoders.mp4 17.2 MB
  • 28. Explore Gradient Descent & Back Propagation/2. Gradient Descent.mp4 17.2 MB
  • 63. Examine the Fundamentals of HuggingFace/6. ChatGPT Competitor HuggingChat 🦾🤗.mp4 17.0 MB
  • 33. Explore Multi-class Classification with PyTorch/1. Introduction.mp4 15.9 MB
  • 37. Explore TensorFlow Aggregation and Manipulation/5. Tensor Indexing.mp4 15.2 MB
  • 31. Explore Neural Network Classification with PyTorch/6. Visualize Decision Boundary with Probability.mp4 13.8 MB
  • 48. Build a TensorFlow Classifier with Non-Linearity/6. Challenge.mp4 13.3 MB
  • 45. Normalize and Feature Scale Data with TensorFlow/7. What is Normalization and Standardization.mp4 12.0 MB
  • 39. Reshape, Transpose, and Alter TensorFlow Tensors/1. Introduction.mp4 11.9 MB
  • 34. Tune Hyperparameters and Analyze Fit with PyTorch/1. Introduction.mp4 11.8 MB
  • 41. Explore Neural Network Regression with TensorFlow/1. Introduction.mp4 10.8 MB
  • 4. Setup a Machine Learning Development Environment/conda-cheatsheet.pdf 299.1 kB
  • Readme.txt 133 Bytes
  • 3. Define What is Machine Learning/lumber_prediction_line.ipynb.txt 85 Bytes

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