Deep Learning Roadmap

Basic Level

Essential mathematics like linear algebra, calculus, statistics, probability required to understand neural networks.

Linear Algebra - Khan Academy Calculus - Khan Academy

Python with libraries like NumPy, Pandas, Matplotlib, and basic programming concepts.

Python Getting Started NumPy Quickstart

Understanding neural network concepts like perceptron, forward/backward propagation, etc.

Neural Networks Course 3Blue1Brown Neural Networks

Git is a version control system for tracking changes in source code. GitHub is a platform for hosting repositories and collaborating on projects.

Official Git Documentation GitHub Docs

Frameworks for building and training deep neural networks.

TensorFlow Tutorials PyTorch Tutorials

A type of neural network specialized for processing visual data.

CNN Specialization CS231n CNN Guide

A type of neural network specialized for analyzing sequential data.

Sequence Models Course Understanding LSTM Networks

Using pre-trained models to improve performance on new tasks.

TensorFlow Transfer Learning PyTorch Transfer Learning

Models for generating content like images, audio, etc.

GANs Specialization GANs Implementation

Advanced models for natural language processing like BERT, GPT.

Transformer Models Course Hugging Face Course

A type of ML where an agent learns by interacting with an environment.

RL Specialization OpenAI Spinning Up

Integrating ML with operations using tools like MLflow, Kubeflow, etc.

MLflow Documentation Kubeflow Documentation