Deep Learning 101 - Zero to Hero for Deep Learning

Learn the fundamentals of deep learning from scratch in this comprehensive 2 hour and 29 minute course that takes you from zero to hero. Build your first neural network and master essential concepts including backpropagation, activation functions, optimizers, and loss functions. Explore advanced techniques such as batch normalization, embeddings, and transfer learning while diving into natural language processing applications from n-grams to large language models. Understand critical practical considerations including training data requirements and hyperparameter tuning to develop a solid foundation in deep learning principles and implementation.

Syllabus

Building your first Neural Network
Backpropagation in Neural Networks - EXPLAINED!
Activation functions in neural networks
Optimizers in Neural Networks - EXPLAINED!
Loss functions in Neural Networks - EXPLAINED!
Batch Normalization in neural networks - EXPLAINED!
Embeddings - EXPLAINED!
Transfer Learning - EXPLAINED!
NLP with Neural Networks | ngram to LLMs
How much training data does a neural network need?
Hyper parameters - EXPLAINED!