yash-kavaiya / 100daysofdeeplearning

100daysofdeeplearning

1. ANN

1. Artificial Neural Networks(ANN) a. Basics • What is Deep Learning • Deep Learning Vs Machine Learning • Why deep learning is getting famous now? • Deep Learning Application • Deep Learning Types • History of Deep Learning b. Perceptron • What is a Perceptron • Perceptron Vs Neuron • Prediction in a Perceptron • Training in a Perceptron • Problem with the Perceptron c. MLP • Intuition of MLP • MLP Notation • Prediction in MLP| d. Training an MLP • Gradient Descent • Backpropagation e. Practical with Keras • CPU Vs GPU • Installation • Regression using Keras • Classification usina Keras

f. How to improve an ANN • Vanishing Gradients • Exploding Gradients • Dropouts • Regularization • Weight Initialization • Optimizers • Gradient Checking and Clipping • Batch Normalization • Hyperparameter Tuning g. Advanced Topics • Callbacks • Tensorboard • Pretrained Models • Kera Functional API • Saving and Loading a Keras model

h. Project • End to End Project • AWS deployment

2. CNN
3. RNN
4. Autoencoders
5. GANS
6. Object detection
7. Image Segmentation
8. Transformers