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01. Introduction to Deep Learning

Name		Name	Last commit message	Last commit date
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.ipynb_checkpoints		.ipynb_checkpoints
images		images
1.01 What is Deep Learning?.ipynb		1.01 What is Deep Learning?.ipynb
1.02 Biological and Artificial Neurons.ipynb		1.02 Biological and Artificial Neurons.ipynb
1.03 ANN and its layers.ipynb		1.03 ANN and its layers.ipynb
1.04 Exploring activation functions.ipynb		1.04 Exploring activation functions.ipynb
1.09 Building Neural Network from scratch.ipynb		1.09 Building Neural Network from scratch.ipynb
README.md		README.md

1.1. What is Deep Learning?
1.2. Biological and Artifical Neurons
1.3. ANN and its Layers
1.4. Exploring Activation Functions
1.5. Forward Propagation in ANN
1.6. How does ANN learn?
- 1.6.1. Backward Propagation
- 1.6.2. Gradient Descent
1.7. Debugging Gradient Descent with Gradient Checking
- 1.7.1 Implementing Gradient Checking
1.8. Putting it all together
1.9. Building Neural Network from Scratch