The amateur’s guide to explore Deep Learning

Hello There !!!

I am an AI enthusiast and constantly exploring Deep Learning. These are my notes and codes that I constantly forget. These topics are mostly coded by me but referenced from many Authors, Youtube videos, Books and free articles over the internet, So even if you want to reuse these notes you can, free of cost 😊.

This guide is generally verified by my peers and the people that I know in this field and mostly by the readers of it. Please feel free to reach out to me if there is any issue the the documentation.

Contact Me

email	nishantbaheti.it19@gmail.com
github	https://www.github.com/nishantbaheti
linkedin	https://www.linkedin.com/in/nishantbaheti/
ML GUIDE	https://mlguidebook.com
Understand Any Topic For Free	https://topmate.io/nishantbaheti/474284

Implementation

• Logistic Regression From Scratch
  • References
  • Dataset
  • Metrics
  • Activation Function
  • Architecture
  • Gradient Descent Algorithm
• Neural Network From Scratch
  • References
  • Dataset
  • Metrics
  • Activation Function
  • Architecture
  • Gradient Descent Algorithm
• Transformer From Scratch
  • References
  • Architecture
  • Embedding
  • Positional Encoding
  • Scaled Dot-Product Attention (SingleHead)
  • MultiHead Attention
  • Masked-MultiHead Attention (Optional)
  • Self Attention Vs Cross Attention
  • Add & Norm (Convergence Optimizations)
  • Position-Wise Feed Forward Network
  • Repeated Block
  • Final Linear Layer and Softmax
• AutoGrad From Scrach
  • References
  • Differentiability

Architecture Components

• Architecture
• Symbols & Naming Conventions
• Flow
• Shapes
• Dense Layer
  • Forward
  • Backward
  • Model
• Activation Functions
  • Sigmoid
  • Stepwise
  • Relu
  • Leaky Relu
  • Softplus
  • Hyperbolic Tangent(Tanh)
  • Softmax
  • Gaussian
• Loss
  • Categorical Cross Entropy
• Optimization Algortihms
  • Gradient Descent
  • Mini Batch Gradient Descent

pytorch

• Pytorch Basics
  • References
  • Building
• Pytorch Tensor
• Autograd in Pytorch
  • Reference

Intuition

• What is log
• Regression Intuition
  • Fitting a linear regression model
  • lets try something with Neural Networks
  • lets try with a little bit complex pattern
  • sine wave with a nerual network
• Classification Boundaries
  • Basic Classification
  • Easy Spiral Classification
  • Complex Spiral Classification

Additional Docs

• ML Guide Book
• Reco Guide Book
• NLP Guide Book
• Python Guide Book
• mightypy
• graphpkg

Indices and tables

• Index

• Module Index

• Search Page