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.

The fastai deep learning library

A game theoretic approach to explain the output of any machine learning model.

A simple screen parsing tool towards pure vision based GUI agent

In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

Neural Networks: Zero to Hero

This repository contains the source code for the paper First Order Motion Model for Image Animation

Image restoration with neural networks but without learning.

Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion

Portfolio and risk analytics in Python

From the basics to slightly more interesting applications of Tensorflow

Efficient Image Captioning code in Torch, runs on GPU

Tacotron 2 - PyTorch implementation with faster-than-realtime inference

Performance analysis of predictive (alpha) stock factors

Singing Voice Conversion via diffusion model

TensorFlow Tutorial for Time Series Prediction

IPython kernel for Torch with visualization and plotting

How to create custom COCO data set for instance segmentation

This is the code for "How to Do Win Slot Machines - Intro to Deep Learning #13' by Siraj Raval on YouTube

Nautical Object Detection using Detectron2 for Instance Segmentation Trained on Nautical Objects (buoys, ships and land).

A collection of python scripts of notebooks that I find useful