by Suf | Nov 23, 2024 | Data Science, Machine Learning, PyTorch
Table of Contents Introduction The MNIST Challenge Prerequisites Dataset Overview Exploratory Data Analysis (EDA) Building the Model Training the Model Model Evaluation Results Visualization Error Analysis Conclusion and Future Work Introduction Logistic regression is...
by Suf | Nov 21, 2024 | Machine Learning, Programming, PyTorch
Introduction ReLU (Rectified Linear Unit) revolutionized deep learning with its simplicity and efficiency, becoming the go-to activation function for neural networks. Defined as f(x) = max(0, x), ReLU activates only positive inputs, solving issues like vanishing...
by Suf | Nov 17, 2024 | Machine Learning, Programming, Python, PyTorch
Contents Introduction Understanding the Error Common Causes Example to Reproduce Error Inception v3 Specific Requirements Complete Working Solution Best Practices Introduction When working with pre-trained models in PyTorch, particularly convolutional neural networks,...
by Suf | Nov 17, 2024 | Machine Learning, Programming, PyTorch
Contents Introduction Reproducing the Error Fixing the Error Visualizing the Batch Dimension Why Batch Dimensions Are Important Common Mistakes to Avoid Debugging Tensor Shapes Further Reading Summary Introduction One common error when working with pre-trained PyTorch...
by Suf | Nov 17, 2024 | Machine Learning, Programming, Python, PyTorch
Table of Contents Introduction Brief Definitions of reshape() and view() Key Differences Between reshape() and view() Visual Matrix Examples Common Operations and Best Practices Troubleshooting Conclusion Introduction In PyTorch, reshape() and view() are fundamental...
