Deep Learning
UNIT I
Deep Learning: Fundamentals, Introduction, Building Block of Neural
Networks, Layers, MLPs, Forward pass, backward pass, class, trainer
and optimizer, The Vanishing and Exploding Gradient
Problems, Difficulties in Convergence, Local and Spurious Optima,
Preprocessing, Momentum, learning
rate Decay, Weight Initialization, Regularization, Dropout, SoftMax, Cross
Entropy loss function, Activation
Functions.
👉Deep Learning: UNIT 1 (A) Notes: Deep Learning: Fundamentals Part 1 Notes
👉Deep Learning: UNIT 1 (A) PPTs: Deep Learning Fundamentals Part 1 PPTs
👉Deep Learning: Unit 1 (B) Notes: Deep Learning Fundamentals Part 2 Notes
👉Deep Learning: UNIT 1 (B): Deep Learning: Fundamentals Part2 PPTs
👉Deep Learning: UNIT 1: Deep Learning - Fundamentals: Long Answer Questions
👉Deep Learning: UNIT 1: Deep Learning - Fundamentals : Short Answer Questions
UNIT II
CNN: Introduction, striding
and padding, pooling
layers, structure, operations and prediction of CNN with layers, CNN -Case study
with MNIST, CNN VS
Fully Connected.
👉Deep Learning: UNIT-2: CNN PPTs
👉Deep Learning: UNIT-2: CNN Notes
👉Deep Learning: UNIT 2: CNN : Long Answer Questions
👉Deep Learning: UNIT 2: CNN: Short Answer Questions
UNIT III
RNN: Handling Branches, Layers, Nodes, Essential Elements-Vanilla RNNs, GRUs, LSTM
👉Deep Learning: UNIT 3 (A): RNN: Notes
👉Deep Learning: UNIT 3 (A) : RNN : PPTs
👉Deep Learning: UNIT- 3: RNN: Long Answer Questions
👉Deep Learning: UNIT 3 : RNN : Short Answer Questions
UNIT IV
Autoencoders: Denoising Autoencoders, Sparse Autoencoders, Deep Autoencoders, Variational Autoencoders, GANS
👉Deep Learning: UNIT 4: Autoencoders PPTs
👉Deep Learning: UNIT 4: Autoencoders NOTEs
UNIT V
Transfer Learning- Types, Methodologies, Diving into Transfer Learning, Challenges
👉Deep Learning : UNIT 5: Transfer Learning Notes
👉Deep Learning : UNIT 5: Transfer Learning PPTs
Text Books:
1. Seth Weidman, “Deep Learning from Scratch”, O'Reilly
Media, Inc., 2019
2. Ian Goodfellow, Yoshua Bengio and Aaron Courville, “Deep Learning” , MIT Press, 2015
3. Dipanjan Sarkar, Raghav Bali, “Transfer Learning in Action”, Manning Publications, 2021
Reference Books:
1. Giancarlo Zaccone,
Md. Rezaul Karim,
Ahmed Menshawy "Deep Learning with TensorFlow: Explore neural networks with Python", Packt Publisher, 2017.
2. Antonio Gulli,
Sujit Pal, "Deep Learning with Keras", Packt Publishers, 2017.
3. Francois Chollet,
"Deep Learning with Python",
Manning Publications, 2017.
