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Deep Learning

Before starting to learn Deep Learning, make sure to first learn basics of Machine Learning

ANN basics Part 1 ANN basics Part 2 ANN basics Part 3 ANN basics Part 4 Advanced ANN Part 1 Advanced ANN Part 2 Advanced ANN Part 3 Advanced ANN Part 4 Advanced ANN Playlist Advanced ANN Part 5 Advanced ANN Part 6

Boosting Algorithms Part 1 Boosting Algorithms Part 2 Boosting Algorithms Part 3 Boosting Algorithms Part 4

Basic CNN Model Part 1 Basic CNN Model Part 2 Basic CNN Model Part 3 Basic CNN Model Part 4 Backprop in CNN

CNN Architectures Part 1

Autoencoders Part 1 GANs Part 1

Practical Considerations Part 1

RNN & LSTM Theory Part 1

RNN & LSTM Practical Part 1

Transformer Architecture and LLMs Part 1

LLM Pre-Training Part 1 LLM Pre-Training Part 2 LLM Pre-Training Part 3 LLM Pre-Training Part 4 LLM Pre-Training Part 5

Fine Tuning LLMs Part 1 Fine Tuning LLMs Part 2

RAG Part 1 RAG Part 2

Image Captioning, Text to Image Part 1 Image Captioning, Text to Image Part 2

Deployment Part 1

ANN basics Part 1

What You Will Learn

Basic ANN concepts

Content Covered

Introduction to basic Artificial Neural Networks.

Resources

Universal Approximation Theorem
Embedding layer vs Dense layer
Difference between Brain and ANN
Difference between Brain and ANN (Medium)
PyTorch

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