Official inference framework for 1-bit LLMs

Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

This repository is the source code for examples and illustrations discussed in the book - A Simple Introduction to Retrieval Augmented Generation

Welcome to the LLMs Interview Prep Guide! This GitHub repository offers a curated set of interview questions and answers tailored for Data Scientists. Enhance your understanding of Large Language M…

Common used path planning algorithms with animations.

Python sample codes for robotics algorithms.

This project is personal fitness trainer

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Some Python Implementations of the Kalman Filter

PyTorch tutorials.

Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.

Pre-trained NFNets with 99% of the accuracy of the official paper "High-Performance Large-Scale Image Recognition Without Normalization".

High Performance Tensorflow Data Pipeline with State of Art Augmentations and low level optimizations.

Fast and Accurate ML in 3 Lines of Code

Implementing polyp segmentation using the U-Net and CVC-612 dataset.

List of projects related to Natural Language Processing (NLP) that make a geek smile for they exist

VIP cheatsheets for Stanford's CS 229 Machine Learning

Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.

Classification of Breast Cancer diagnosis Using Support Vector Machines

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models

Deep Learning Papers on Medical Image Analysis

Collection of Keras models used for classification

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

An Personal Note for DS/ML interview questions

Machine Learning and Computer Vision Engineer - Technical Interview Questions

Dog and cat image classifier with deep learning

SSD: Single Shot MultiBox Detector in keras.