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AI_DL_Assignment / 6. Neural Networks Explained

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1. Neural Networks Chapter Overview.srt

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10. Epochs, Iterations and Batch Sizes.srt

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11. Measuring Performance and the Confusion Matrix.srt

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12. Review and Best Practices.srt

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2. Machine Learning Overview.srt

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3. Neural Networks Explained.srt

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4. Forward Propagation.srt

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5. Activation Functions.srt

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6. Training Part 1 – Loss Functions.srt

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7. Training Part 2 – Backpropagation and Gradient Descent.srt

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8. Backpropagation & Learning Rates – A Worked Example.srt

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9. Regularization, Overfitting, Generalization and Test Datasets.srt

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