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.

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

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

Lab materials for the Full Stack Deep Learning Course

Keras implementation of CNN, DeepConvLSTM, and SDAE and LightGBM for sensor-based Human Activity Recognition (HAR).

Repo for the Deep Learning Nanodegree Foundations program.

LLM, RAG, LoRA, QLoRA, langchain, Llama, OpenAI