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.
๐Deep Learning: UNIT 1 (A) Notes: Deep Learning: Fundamentals Part 1 Notes
๐Deep Learning: UNIT 1 (A) PPTs: Deep Learning Fundamentals Part 1 PPTs
๐Deep Learning: Unit 1 (B) Notes: Deep Learning Fundamentals Part 2 Notes
๐Deep Learning: UNIT 1 (B): Deep Learning: Fundamentals Part2 PPTs
๐Deep Learning: UNIT 1: Deep Learning - Fundamentals: Long Answer Questions
๐Deep 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.
๐Deep Learning: UNIT-2: CNN PPTs
๐Deep Learning: UNIT-2: CNN Notes
๐Deep Learning: UNIT 2: CNN : Long Answer Questions
๐Deep Learning: UNIT 2: CNN: Short Answer Questions
UNIT III
RNN: Handling Branches, Layers, Nodes, Essential Elements-Vanilla RNNs, GRUs, LSTM
๐Deep Learning: UNIT 3 (A): RNN: Notes
๐Deep Learning: UNIT 3 (A) : RNN : PPTs
๐Deep Learning: UNIT- 3: RNN: Long Answer Questions
๐Deep Learning: UNIT 3 : RNN : Short Answer Questions
UNIT IV
Autoencoders: Denoising Autoencoders, Sparse Autoencoders, Deep Autoencoders, Variational Autoencoders, GANS
๐Deep Learning: UNIT 4: Autoencoders PPTs
๐Deep Learning: UNIT 4: Autoencoders NOTEs
UNIT V
Transfer Learning- Types, Methodologies, Diving into Transfer Learning, Challenges
๐Deep Learning : UNIT 5: Transfer Learning Notes
๐Deep Learning : UNIT 5: Transfer Learning PPTs
Text Books:
1. Seth Weidman, โDeep Learning from Scratchโ, O'Reilly
Media, Inc., 2019
2. Ian Goodfellow, Yoshua Bengio and Aaron Courville, โDeep Learningโ , MIT Press, 2015
3. Dipanjan Sarkar, Raghav Bali, โTransfer Learning in Actionโ, 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.
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