Syllabus

UNIT – I
Basics related to Calculus, Linear Algebra, Python 3, probability and optimization.

UNIT – II
Gradient descent, cost function, Stochastic gradient descent, Adam, Momentum, Neural Networks, Deep Neural Networks, hyperparameter tuning, Regularization.

UNIT – III
Basics of CNNs. Detailed understanding of LeNet and Alexnet Architectures, ResNet, VGG-16, VGG-19. Their implementations.

UNIT – IV
Basics of RNNs. Detailed understanding of sequence models, text generation, neural machine translation, and speech.

Understand the fundamentals of feedforward, recurrent and convolutional neural networks and apply them to solve various real-world problems.

Develop a deeper understanding of different optimization algorithms, gradient descent, stochastic gradient descent and recent developments like ADAM and RMSprop.

Explore state-of-the-art architectures (CNN, LSTM, GRU, Bidirectional Models and Deep Generative Models) and learn transfer learning with feature and decision-level fusion.

Learn to improve the computational efficiency and performance of DL models for a specific problem by optimizing hyperparameters and employing GPUs

1. Develop in-depth understanding of the key deep learning models and concepts.
2. Gain practical skills and theoretical knowledge necessary to apply deep learning techniques to a wide range of problems.
3. Improve deep learning models' performance (tuning hyperparameters) and computational efficiency (using GPUs) for real-world problems.
4. Determining an appropriate deep learning model for an application.

A. Zhang, Z.C. Lipton, M. Li, A.J. Smola, Dive into Deep Learning, Cambridge University Press , Website: https://d2l.ai

Ian Goodfellow, Yoshua Bengio, Aaron Courville, Deep Learning, MIT Press , Website: https://www.deeplearningbook.org/

Francois Chollet, Deep Learning with Python, Manning Publishers

E. Stevens, L. Antiga, T. Viehmann, Deep Learning with PyTorch, Manning Publishers

IEEE Transactions on Pattern Analysis and Machine Intelligence

AAAI Conference on Artificial Intelligence