[FCSNEW.NET] Udemy - Practical Deep Learning Master PyTorch in 15 Days

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[FCSNEW.NET] Udemy - Practical Deep Learning Master PyTorch in 15 Days

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文件列表

  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/2. good.zip 946.5 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/2. defective.zip 916.0 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/13. Part 4 Evaluating Model Performance and Addressing Overfitting.mp4 311.6 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/20. Demonstrating Overfitting in Neural Network Training.mp4 306.9 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/6. Investigating Key Data Relationships for Model Training.mp4 275.4 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/19. Using the Trained Model to Predict Tire Quality.mp4 261.2 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/5. Using ResNet-50 to Classify an Image of a Cat.mp4 259.4 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/28. Optional extra Application of Overfitting Detection and Model Finalization.mp4 253.7 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/12. Evaluating Model with Key Performance Metrics.mp4 247.5 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/5. Exploring the Used Car Dataset with Pandas.mp4 242.3 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/15. Implementing Training and Validation Data Splits in Python.mp4 231.1 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/16. Integrating Data Augmentation into Model Training for Improved Accuracy.mp4 226.5 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/23. Optional extra Applying a Neural Network to Custom Images.mp4 224.2 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/8. Training a Neuron 1 Preparing and Optimizing.mp4 223.7 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/8. Optional Applying a Single Neuron to Student Exam Data.mp4 222.6 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/7. Optional extra Exploring the ResNet Research Paper.mp4 220.4 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/9. Building and Training Our First Neural Network.mp4 218.5 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/14. The dtype of a Tensor.mp4 214.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/19. Optional extra Generating Embeddings with BART for Spam Detection.mp4 214.1 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/13. Evaluating a Neural Network for Multi-Class Classification.mp4 212.5 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/7. Part 1 Implementing a CNN.mp4 210.9 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/16. Implementing Input Normalization in PyTorch for Improved Predictions.mp4 209.8 MB
  • 08. Day 8 Exercise Loan Approval Classification/4. Solution Part 2 Building and Training the Loan Approval Model.mp4 205.8 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/8. Preparing Data for ResNet Training.mp4 203.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/3. Using Count Vectorizer to Transform Text into Numerical Data.mp4 201.8 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/5. Building a Binary Classifier for 0 Detection.mp4 190.6 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/10. Training the Model Initial Setup and Challenges.mp4 188.7 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/18. Implementing Mini-Batch Learning for Efficient Training.mp4 187.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/2. Exploring and Preprocessing the SMS Spam Dataset.mp4 187.4 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/10. Part 2 Building a Transfer Learning Model for Tire Quality Prediction.mp4 185.6 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/6. Evaluating the Binary Classifier for 0 Detection.mp4 181.4 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/21. Optional extra Integrating Embeddings into the Spam Filter.mp4 178.3 MB
  • 08. Day 8 Exercise Loan Approval Classification/2. Exploring the Loan Approval Dataset.mp4 176.9 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/13. Creating a Model.mp4 176.8 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/4. An Introduction to ResNet in Transfer Learning.mp4 176.0 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/11. Reducing CNN Complexity with Max Pooling.mp4 171.9 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/13. Batch Learning and Making Predictions with PyTorch.mp4 170.1 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/9. Structuring Data for Model Input and Running an Initial Prediction.mp4 168.4 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/19. Saving and Loading Model in PyTorch.mp4 167.0 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/21. Strategies to Counter Overfitting.mp4 166.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/20. Day 12 Advancing CNN Complexity.mp4 166.4 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/15. Data Augmentation for Combating Overfitting.mp4 166.3 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/12. Day 14 Part 3 Training the Transfer Learning Model.mp4 165.4 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/2. Installing the necessary tools (Windows).mp4 165.0 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/3. Getting Started with Jupyter Interactive Python Programming.mp4 158.8 MB
  • 08. Day 8 Exercise Loan Approval Classification/1. Introduction to Loan Approval Prediction.mp4 158.5 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/6. Understanding Gradient Descent for Neuron Optimization.mp4 158.0 MB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/5. Integrating Gradio with PyTorch for Predictions.mp4 157.2 MB
  • 08. Day 8 Exercise Loan Approval Classification/3. Solution Part 1 Preparing Data for the Loan Approval Model.mp4 154.1 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/18. Experimenting with Training Parameters Through Loss Visualization.mp4 153.4 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/16. Optimizing Tensor Computations on GPU.mp4 152.7 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/11. Training a Neural Network for Multi-Class Classification.mp4 146.7 MB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/6. Deploying Gradio for Real-World Tire Predictions.mp4 145.4 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/3. Optional extra Exploring Nonlinearity and Its Impact on Neural Networks.mp4 145.3 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/3. Installing the necessary tools (Linux).mp4 140.1 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/17. Experimenting with Different Neural Network Architectures.mp4 138.4 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/4. Installing the necessary tools (macOS).mp4 135.9 MB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/3. Uploading and Processing Images with Gradio.mp4 134.8 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/9. Part 1 Customizing ResNet-50 for Tire Quality Prediction.mp4 134.3 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/8. Developing a First Neuron.mp4 134.3 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/20. Testing Approaches for Tire Model Deployment.mp4 134.3 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/3. From Dataset to DataLoader Preparing Data for Neural Network.mp4 133.1 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/16. Optimizing Training with Adam.mp4 130.6 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/8. Multi-Class Classification in Neural Networks.mp4 128.1 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/2. Exploring MNIST Data with TorchVision.mp4 128.1 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/6. Training the Model for Spam Classification.mp4 124.9 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/12. Matrix in a Tensor.mp4 124.4 MB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/2. Getting Started with Gradio for Simple AI Apps.mp4 124.2 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/1. Course Materials.zip 122.2 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/4. How Neuron Learns A Scalable Approach.mp4 122.2 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/2. What is learning.mp4 121.2 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/15. Day 8 Introducing ReLU Activation Function.mp4 120.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/18. Accelerating CNN Execution Speed with GPU.mp4 119.7 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/13. Implementing Output Normalization in PyTorch for Consistent Predictions.mp4 118.7 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/5. Optional Decoding the Mathematics of Backpropagation.mp4 116.7 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/8. Part 2 Advancing CNN Implementation.mp4 114.8 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/20. Optional extra Building a Function to Generate Embeddings for Spam Detection.mp4 114.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/17. Running Simple Model on GPU.mp4 113.6 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/22. Solution Adding an Additional Column to the Model.mp4 113.1 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/18. Optional extra Improving Spam Detection with Large Language Model Embeddings.mp4 113.0 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/10. Training a Neuron 2 Iterative Learning and Adjustments.mp4 111.2 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/5. Running a first file.mp4 109.4 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/13. Simplifying the Code with nn.Sequential.mp4 109.4 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/25. Refining CNN with Batch Normalization.mp4 104.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/24. Optimizing CNN with Dropout Layers.mp4 104.4 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/12. Day 4 Understanding Output Normalization for Stable Learning.mp4 102.4 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/2. Optional Understanding Activation Functions in Neural Networks.mp4 102.1 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/27. Optional Understanding the Mathematics of Batch Normalization.mp4 97.5 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/5. Optional Extra Exploring TF-IDF Vectorizer for Improved Text Preprocessing.mp4 96.8 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/21. Exercise Adding an Additional Column to the Model.mp4 96.6 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/24. Optional extra Overcoming Preprocessing Challenges in Model Application.mp4 91.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/10. Switching to Binary Cross Entropy Loss for Effective Training.mp4 90.8 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/14. Optional Enabling CUDA on NVIDIA GPUs.mp4 90.1 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/12. The Importance of Mean Squared Error in Model Training.mp4 88.2 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/1. Day 13 Introduction to Transfer Learning and Tire Quality Prediction.mp4 87.6 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/16. Applying and Evaluating the Model on Fresh Data.mp4 84.5 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/11. Unpacking Tensors, Accessing Vectors.mp4 84.1 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/21. Enhancing CNN Performance with Increased Filter Complexity.mp4 81.5 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/12. Evaluating Neural Network Performance.mp4 81.5 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/19. Understanding Overfitting in Neural Networks.mp4 77.3 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/7. Analyzing Student Performance Data for Exam Predictions.mp4 75.0 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/19. Optimizing Loss Tracking in Mini-Batch Training.mp4 74.4 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/8. Finalizing Input and Target Columns for Model Training.mp4 72.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/14. Day 6 Understanding Training, Validation and Test Data in Model Development.mp4 72.0 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/11. Using BCE with Sigmoid for Loss Calculation and Prediction.mp4 69.3 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/16. Applying Softmax in Neural Network.mp4 67.4 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/8. Understanding the Sigmoid Activation Function for Probability Output.mp4 66.7 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/15. Leveraging Google Colab's Free GPU.mp4 62.1 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/15. Understanding Input Normalization for Consistent Training.mp4 60.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/3. Optional Assessing Previous Model Performance on Fashion MNIST Data.mp4 59.3 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/2. Overview of the Used Car Price Dataset.mp4 59.2 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/18. Adapting Model Weights for Universal Compatibility.mp4 57.0 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/23. Introducing Dropout for Improved Generalization.mp4 56.4 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/4. Exploring Edge Detection with the Sobel Operator.mp4 56.2 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/15. Day 10 Understanding Softmax for Class Probability Normalization.mp4 52.6 MB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/1. Introduction to Deploying AI Models with Gradio.mp4 52.3 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/4. Understanding Backpropagation in Neural Networks.mp4 52.0 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/9. Understanding One-Hot Encoding.mp4 50.7 MB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/3. Exploring the Tire Quality Dataset.mp4 49.5 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/6. What is a model.mp4 47.2 MB
  • 14. Closing words/1. Closing words.mp4 46.5 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/2. Exploring Fashion MNIST Data.mp4 44.6 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/1. Day 11 Introduction to Convolutional Neural Networks.mp4 42.8 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/13. Utilizing GPU Acceleration with PyTorch.mp4 41.1 MB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/6. Understanding the Structure of Convolutional Neural Networks for Edge Detection.mp4 38.3 MB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/1. Day 7 From Single Neuron to Neural Networks.mp4 33.9 MB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/1. Day 3 Introduction to Predicting Used Car Prices.mp4 30.5 MB
  • 01. Introduction/1. Overview Practical Deep Learning.mp4 26.9 MB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/1. Day 5 Introduction to Spam Detection.mp4 26.9 MB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/1. Day 9 Introduction to Handwritten Digit Classification.mp4 20.4 MB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/10. A First Tensor.mp4 19.8 MB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/1. Introduction to Neuron Training.mp4 16.9 MB
  • 13. Day 15 Exam/1.2 PRACTICE EXAM Test your knowledge so far (22).html 116.9 kB
  • 06. Day 6 Exam/1.1 PRACTICE EXAM Test your knowledge so far (12).html 103.5 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/29.38 Test your knowledge on Key CNN Techniques.html 32.3 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/12. geogebra.ggb 31.7 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/21.43 Test your knowledge on Tire Quality Prediction and Transfer Learning.html 30.4 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/14.7 Test your knowledge on Batch Learning, Loss Functions and Training Process.html 27.5 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/20.24 Test your knowledge on Essential Neural Network Concepts.html 27.5 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/25.31 Test your knowledge on Multi-Class Classifier Fundamentals.html 27.3 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/20.13 Test your knowledge on Data Preparation, Model Training and Evaluation.html 25.7 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/23.19 Test your knowledge on Spam Detection Techniques.html 25.6 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/22.18 Optional extra Test your knowledge on Enhancing Detection with LLM Embeddings.html 23.0 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/13. Part 4 Evaluating Model Performance and Addressing Overfitting.vtt 22.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/20. Demonstrating Overfitting in Neural Network Training.vtt 22.4 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/9.33 Test your knowledge on CNN Architecture and Functionality.html 22.3 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/9.2 Test Your Knowledge of the Structure and Mathematical Model of a Neuron.html 22.0 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/4.14 Test your knowledge on Spam Detection and Text Preprocessing.html 22.0 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/13.16 Test your knowledge on Loss Functions and Evaluation Metrics in Spam Detection.html 21.9 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/7.9 Test your knowledge on Data Exploration and Preparation with Pandas.html 21.8 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/9.15 Test your knowledge on Model Training and Sigmoid Function for Spam Detection.html 21.7 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/4.25 Test your knowledge on Data Preparation for Neural Network Training.html 21.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/26.37 Test your knowledge on Dropout and Batch Normalization.html 21.6 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/17.17 Test your knowledge on Data Segmentation in Model Development.html 21.6 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/11.10 Test your knowledge on Data Preparation and Initial Neuron Training Steps.html 21.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/19.35 Test your knowledge on Utilizing GPUs with PyTorch.html 21.6 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/18.29 Test your knowledge on Softmax and Network Architecture.html 21.6 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/6.39 Test your knowledge of Transfer Learning and ResNet.html 21.5 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/7.26 Test your knowledge on Binary Classifier Essentials.html 21.5 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/10.27 Test your knowledge on Preparing Data for Multi-Class Classification.html 21.2 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/14.11 Test your knowledge on Output Data Normalization.html 21.1 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/22.30 Test your knowledge on Overfitting in Neural Network.html 21.0 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/5.4 Test your knowledge on Loss Functions, Learning Rates, Parameter Initialization.html 21.0 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/11.40 Test your knowledge on Preparing and Modifying ResNet for Transfer Learning.html 20.9 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/5.32 Test your knowledge on CNN Basics and Image Processing.html 20.6 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/11.21 Test your knowledge on Data Analysis and Neural Network Training.html 20.5 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/17.42 Test your knowledge on Enhancing Models with Data Augmentation.html 20.5 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/4.44 Test your knowledge on Gradio and AI Model Integration.html 20.4 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/14.41 Test your knowledge on Training and Evaluating a Transfer Learning Model.html 20.3 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/6.20 Test your knowledge on Neural Network Fundamentals.html 20.2 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/5. Using ResNet-50 to Classify an Image of a Cat.vtt 20.2 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/17.23 Test your knowledge on Optimizing Neural Networks with ReLU and Adam.html 20.2 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/4.8 Test your knowledge on Used Car Dataset and Jupyter.html 20.1 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/14.22 Test your knowledge on Neural Network Application Techniques.html 20.1 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/7.1 Test your knowledge about the Foundations of Machine Learning and Models.html 19.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/14.28 Test your knowledge on Neural Network Adjustments for Multi-Class Classification.html 19.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/12.34 Test your knowledge on Max Pooling in CNNs.html 19.6 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/6. Investigating Key Data Relationships for Model Training.vtt 19.4 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/11.6 Test your knowledge on Data Handling and Iterative Training.html 19.4 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/7.45 Test your knowledge on Real-World Testing of Gradio Apps.html 19.3 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/22.36 Test your knowledge on CNN Layer Configurations.html 19.3 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/3.3 Test your knowledge on Training Neurons and Learning Parameters.html 19.2 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/12. Evaluating Model with Key Performance Metrics.vtt 19.0 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/2. license.txt 19.0 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/17.12 Test your knowledge on Input Data Normalization.html 18.9 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/28. Optional extra Application of Overfitting Detection and Model Finalization.vtt 18.6 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/15. Implementing Training and Validation Data Splits in Python.vtt 18.5 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/19. Using the Trained Model to Predict Tire Quality.vtt 18.1 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/7.5 Test your knowledge on Gradient Descent.html 17.6 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/5. Exploring the Used Car Dataset with Pandas.vtt 17.6 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/23. Optional extra Applying a Neural Network to Custom Images.vtt 17.5 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/13. Evaluating a Neural Network for Multi-Class Classification.vtt 17.5 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/9. Building and Training Our First Neural Network.vtt 17.4 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/8. Training a Neuron 1 Preparing and Optimizing.vtt 17.1 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/7. Optional extra Exploring the ResNet Research Paper.vtt 16.7 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/16. Implementing Input Normalization in PyTorch for Improved Predictions.vtt 16.6 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/8. Optional Applying a Single Neuron to Student Exam Data.vtt 16.6 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/16. Integrating Data Augmentation into Model Training for Improved Accuracy.vtt 16.5 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/7. Part 1 Implementing a CNN.vtt 16.5 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/19. Optional extra Generating Embeddings with BART for Spam Detection.vtt 16.2 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/3. Using Count Vectorizer to Transform Text into Numerical Data.vtt 15.4 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/2. Exploring and Preprocessing the SMS Spam Dataset.vtt 15.3 kB
  • 08. Day 8 Exercise Loan Approval Classification/4. Solution Part 2 Building and Training the Loan Approval Model.vtt 15.1 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/14. The dtype of a Tensor.vtt 15.0 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/10. Training the Model Initial Setup and Challenges.vtt 15.0 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/6. Evaluating the Binary Classifier for 0 Detection.vtt 14.1 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/10. Part 2 Building a Transfer Learning Model for Tire Quality Prediction.vtt 14.0 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/8. Preparing Data for ResNet Training.vtt 13.9 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/21. Optional extra Integrating Embeddings into the Spam Filter.vtt 13.9 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/9. Structuring Data for Model Input and Running an Initial Prediction.vtt 13.6 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/19. Saving and Loading Model in PyTorch.vtt 13.5 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/4. An Introduction to ResNet in Transfer Learning.vtt 12.8 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/13. Creating a Model.vtt 12.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/21. Strategies to Counter Overfitting.vtt 12.7 kB
  • 08. Day 8 Exercise Loan Approval Classification/2. Exploring the Loan Approval Dataset.vtt 12.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/20. Day 12 Advancing CNN Complexity.vtt 12.5 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/11. Reducing CNN Complexity with Max Pooling.vtt 12.5 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/13. Batch Learning and Making Predictions with PyTorch.vtt 12.5 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/12. Day 14 Part 3 Training the Transfer Learning Model.vtt 12.5 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/18. Experimenting with Training Parameters Through Loss Visualization.vtt 12.3 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/11. Training a Neural Network for Multi-Class Classification.vtt 12.2 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/16. Optimizing Tensor Computations on GPU.vtt 12.0 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/6. Understanding Gradient Descent for Neuron Optimization.vtt 11.9 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/2. Installing the necessary tools (Windows).vtt 11.7 kB
  • 08. Day 8 Exercise Loan Approval Classification/3. Solution Part 1 Preparing Data for the Loan Approval Model.vtt 11.7 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/3. Optional extra Exploring Nonlinearity and Its Impact on Neural Networks.vtt 11.6 kB
  • 08. Day 8 Exercise Loan Approval Classification/1. Introduction to Loan Approval Prediction.vtt 11.4 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/5. Integrating Gradio with PyTorch for Predictions.vtt 11.3 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/15. Data Augmentation for Combating Overfitting.vtt 11.3 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/17. Experimenting with Different Neural Network Architectures.vtt 11.1 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/16. Optimizing Training with Adam.vtt 11.0 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/3. Getting Started with Jupyter Interactive Python Programming.vtt 10.8 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/8. Developing a First Neuron.vtt 10.3 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/10. A First Tensor.vtt 10.3 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/3. Uploading and Processing Images with Gradio.vtt 10.2 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/8. Multi-Class Classification in Neural Networks.vtt 9.9 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/3. Installing the necessary tools (Linux).vtt 9.9 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/4. Installing the necessary tools (macOS).vtt 9.9 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/9. Part 1 Customizing ResNet-50 for Tire Quality Prediction.vtt 9.7 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/13. Implementing Output Normalization in PyTorch for Consistent Predictions.vtt 9.6 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/6. Training the Model for Spam Classification.vtt 9.5 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/17. Running Simple Model on GPU.vtt 9.5 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/8. Part 2 Advancing CNN Implementation.vtt 9.5 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/6. Deploying Gradio for Real-World Tire Predictions.vtt 9.4 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/5. Optional Decoding the Mathematics of Backpropagation.vtt 9.3 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/18. Accelerating CNN Execution Speed with GPU.vtt 9.3 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/13. Simplifying the Code with nn.Sequential.vtt 9.3 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/20. Testing Approaches for Tire Model Deployment.vtt 9.2 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/15. Day 8 Introducing ReLU Activation Function.vtt 9.0 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/4. How Neuron Learns A Scalable Approach.vtt 9.0 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/12. Matrix in a Tensor.vtt 9.0 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/2. Getting Started with Gradio for Simple AI Apps.vtt 8.8 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/20. Optional extra Building a Function to Generate Embeddings for Spam Detection.vtt 8.8 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/22. Solution Adding an Additional Column to the Model.vtt 8.8 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/2. What is learning.vtt 8.8 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/10. Training a Neuron 2 Iterative Learning and Adjustments.vtt 8.6 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/5. Running a first file.vtt 8.3 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/2. Optional Understanding Activation Functions in Neural Networks.vtt 8.1 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/12. Day 4 Understanding Output Normalization for Stable Learning.vtt 7.9 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/18. Optional extra Improving Spam Detection with Large Language Model Embeddings.vtt 7.9 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/24. Optimizing CNN with Dropout Layers.vtt 7.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/24. Optional extra Overcoming Preprocessing Challenges in Model Application.vtt 7.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/25. Refining CNN with Batch Normalization.vtt 7.4 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/27. Optional Understanding the Mathematics of Batch Normalization.vtt 7.2 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/14. Optional Enabling CUDA on NVIDIA GPUs.vtt 7.1 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/5. Optional Extra Exploring TF-IDF Vectorizer for Improved Text Preprocessing.vtt 7.1 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/21. Exercise Adding an Additional Column to the Model.vtt 6.8 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/16. Applying and Evaluating the Model on Fresh Data.vtt 6.7 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/12. Evaluating Neural Network Performance.vtt 6.6 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/10. Switching to Binary Cross Entropy Loss for Effective Training.vtt 6.6 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/1. Day 13 Introduction to Transfer Learning and Tire Quality Prediction.vtt 6.4 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/12. The Importance of Mean Squared Error in Model Training.vtt 6.3 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/16. Applying Softmax in Neural Network.vtt 6.0 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/19. Understanding Overfitting in Neural Networks.vtt 5.9 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/21. Enhancing CNN Performance with Increased Filter Complexity.vtt 5.9 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/11. Unpacking Tensors, Accessing Vectors.vtt 5.9 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/11. Using BCE with Sigmoid for Loss Calculation and Prediction.vtt 5.8 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/14. Day 6 Understanding Training, Validation and Test Data in Model Development.vtt 5.7 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/7. Analyzing Student Performance Data for Exam Predictions.vtt 5.5 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/8. Finalizing Input and Target Columns for Model Training.vtt 5.4 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/23. Introducing Dropout for Improved Generalization.vtt 4.8 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/8. Understanding the Sigmoid Activation Function for Probability Output.vtt 4.8 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/2. Overview of the Used Car Price Dataset.vtt 4.7 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/15. Understanding Input Normalization for Consistent Training.vtt 4.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/15. Leveraging Google Colab's Free GPU.vtt 4.6 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/18. Adapting Model Weights for Universal Compatibility.vtt 4.3 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/3. Optional Assessing Previous Model Performance on Fashion MNIST Data.vtt 4.2 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/4. Understanding Backpropagation in Neural Networks.vtt 4.1 kB
  • 01. Introduction/1. Overview Practical Deep Learning.vtt 4.0 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/15. Day 10 Understanding Softmax for Class Probability Normalization.vtt 4.0 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/4. Exploring Edge Detection with the Sobel Operator.vtt 4.0 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/2. Exploring Fashion MNIST Data.vtt 3.9 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/3. Exploring the Tire Quality Dataset.vtt 3.9 kB
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/1. Introduction to Deploying AI Models with Gradio.vtt 3.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/9. Understanding One-Hot Encoding.vtt 3.7 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/6. What is a model.vtt 3.7 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/1. Day 11 Introduction to Convolutional Neural Networks.vtt 3.4 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/13. Utilizing GPU Acceleration with PyTorch.vtt 3.1 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/6. Understanding the Structure of Convolutional Neural Networks for Edge Detection.vtt 2.8 kB
  • 14. Closing words/1. Closing words.vtt 2.7 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/1. Day 7 From Single Neuron to Neural Networks.vtt 2.6 kB
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/1. Day 3 Introduction to Predicting Used Car Prices.vtt 2.4 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/1. Day 5 Introduction to Spam Detection.vtt 2.1 kB
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/2. Preparing the Tire Quality Dataset.html 1.8 kB
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/12. Optimizing Training for Our Neural Network Multi-Class Classifier.html 1.6 kB
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/10. Optimizing Training for Our CNN.html 1.3 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/1. Introduction to Neuron Training.vtt 1.3 kB
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/10. Optimizing Training for Our Neural Network Classifier.html 1.3 kB
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/9. Optimizing Training for Our Neuron Model.html 1.2 kB
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/7. Optimizing Training for Our Neuron Classifier.html 1.0 kB
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/1. Course Materials.html 388 Bytes
  • 0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 01. Introduction/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 01. Introduction/[FCSNEW.NET].url 119 Bytes
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 02. Day 1 Foundations of Neural Networks From Models and Neurons to Tensors/[FCSNEW.NET].url 119 Bytes
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 03. Day 2 Neuron Training From Adjusting Parameters to Batch Learning/[FCSNEW.NET].url 119 Bytes
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 04. Day 3 & 4 Single Neuron Regression Predicting Used Car Prices with PyTorch/[FCSNEW.NET].url 119 Bytes
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 05. Day 5 & 6 Neuron Classifier Spam Detection in SMS/[FCSNEW.NET].url 119 Bytes
  • 06. Day 6 Exam/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 06. Day 6 Exam/[FCSNEW.NET].url 119 Bytes
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 07. Day 7 & 8 Neural Network Classifier Student Exam Results Prediction/[FCSNEW.NET].url 119 Bytes
  • 08. Day 8 Exercise Loan Approval Classification/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 08. Day 8 Exercise Loan Approval Classification/[FCSNEW.NET].url 119 Bytes
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 09. Day 9 & 10 Neural Network for Multi-Class Classification Handwritten Digits/[FCSNEW.NET].url 119 Bytes
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 10. Day 11 & 12 Convolutional Networks Fashion Item Classification (multi-class)/[FCSNEW.NET].url 119 Bytes
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 11. Day 13 & 14 Transfer Learning with ResNet for Tire Quality Prediction/[FCSNEW.NET].url 119 Bytes
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 12. Day 15 Deploying AI Models with Gradio From Setup to Real-World Predictions/[FCSNEW.NET].url 119 Bytes
  • 13. Day 15 Exam/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 13. Day 15 Exam/[FCSNEW.NET].url 119 Bytes
  • 14. Closing words/0. Websites you may like/[FCSNEW.NET].url 119 Bytes
  • 14. Closing words/[FCSNEW.NET].url 119 Bytes
  • [FCSNEW.NET].url 119 Bytes

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