S-FK / McCarthy-Lab-Roadmap

Roadmap to learn Artificial Intelligence for associates at McCarthy Lab@Next Tech Lab

McCarthy Lab Roadmap

Roadmap to learn AI for associates at McCarthy Lab@Next Tech Lab

Data Structures and Algorithms

• Stanford ALgorithms - Coursera or
• Introduction to Algorithms (MIT 6.006)
• Introduction to Computational Thinking and Data Science (MIT 6.0002)
• Learn any one programming language really well and compete on Codechef, Hackerrank, HackerEarth,etc

Data Science Stack

Best places to learn -

• Python - NumPy, Matplotlib and Scipy
• Learning Python 3 The Hard Way
• Python
• NumPy
• Pandas
• Matplotlib and Seaborn

Things you should know

• Linux
• Bash Cheatsheet
• Git - Introduction

Mathematics for Machine Learning

• The Matrix Calculus You Need For Deep Learning - Quick refresher
• Mathematics for Machine Learning - Intermediate
• Numerical Algorithms - Advanced

Machine Learning/AI MOOCs

• Machine Learning - Coursera (Andrew Ng)
• Machine Learning - Coursera (University of Washington)
• UC Berkeley CS188 or
• MIT 6.034
• Machine Learning by Shaurya Bhandari

Note :

• Implement Machine Learning models from scratch using Python
• Once you're comfortable implementing models from scratch, learn scikit-learn and compare performance
• Practice on Kaggle to get your skiills ---> 😎

Machine Learning Books for reference

• Introduction to Statstical Learning
• Elements of Statistical Learning (A little more in-depth than ISLR)
• Pattern Recognition And Machine Learning

Deep Learning MOOCs

• deeplearning.ai - Coursera
• fast.ai

Deep Learning Frameworks

• Keras - To get started
• PyTorch or
• TensorFlow
• Intro to TensorFlow 2.0 for Deep Learning

Note : Learn from official tutorials/docs or GitHub repos which have detailed notebooks like Hvass Labs

Deep Learning Books

• Deep Learning Book

Natural Language Processing

• Natural Language Processing by National Research University Higher School of Economics
• Stanford University's CS224n
• NLP course by Yandex Data School

Reinforcement Learning Tutorials

• David Silver
• Practical Reinforcement Learning
• Practial RL - Yandex Data School

Reinforcement Learning - Libraries

• TensorLayer
• Keras-RL

Reinforcement Learning Books

• Reinforcement Learning – An Introduction

Read blogs, Reddit, follow researchers on Twitter

• Towards Data Science
• Sebastian Ruder
• montreal.ai
• thegradient
• Reddit - Machine Learning
• Reddit - Deep Learning
• https://github.com/ujjwalkarn/Machine-Learning-Tutorials

Miscellaneous

• Learn Flask or Django and make a complete project ---> deploy in on the web

Feel free to make Pull Requests stating why that particular resource should be added.