Repository Index

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

• andrew-ng
• andrew-ng-machine-learning
• coursera
• coursera-assignment

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

• deep-learning
• coursera
• coursera-assignment
• coursera-specialization

TranslatedCovers pre-training data, Tokenizer, Transformer, MoE,distributed training, Scaling Laws, inference & alignment .6 progressive code assignments for full-stack LLM learning

• gpu-programming
• llm
• nlp
• rl

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

• esl
• statistical-learning
• esl-cn
• r

Solutions of Reinforcement Learning, An Introduction

• reinforcement-learning
• exercise-solutions
• self-study
• solutions

Solutions to all the exercises of the Algorithms book by Robert Sedgewick and Kevin Wayne

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Solutions for Elements of Programming Interviews problems written in Golang (work-in-progress)

In this project, the Pacman agent will find paths through his maze world, both to reach a particular location and to collect food efficiently. I implemented general search algorithms such as depth-first, breadth-first, uniform cost, and A* search algorithms which are used to solve navigation problems in the Pacman world.

This project presents a Python-based spam detector program that utilizes the Naive Bayes approach to classify emails as either spam or ham. The system is designed to accurately and efficiently identify spam messages, providing a useful tool for individuals and organizations seeking to manage their email inboxes more effectively.

• anaconda
• jupyter-notebook
• python

Reimplementation of Natural Number Game in Coq

• coq
• lean
• logic
• game