aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

This repository contains all the DSA (Data-Structures, Algorithms, 450 DSA by Love Babbar Bhaiya, FAANG Questions), Technical Subjects (OS + DBMS + SQL + CN + OOPs) Theory+Questions, FAANG Intervie…

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

TensorFlow examples

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Examples and guides for using the Gemini API

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

Data augmentation for NLP

Jupyter notebooks for the Natural Language Processing with Transformers book

Reproducing Yann LeCun 1989 paper "Backpropagation Applied to Handwritten Zip Code Recognition", to my knowledge the earliest real-world application of a neural net trained with backpropagation.

Complete deep learning project developed in Full Stack Deep Learning, Spring 2021

Tensorflow's Fairness Evaluation and Visualization Toolkit

Introductory Statistical Inference

color recognition (convolutional neural network implemented in Keras)

Minimal implementation of adaptive gradient clipping (https://arxiv.org/abs/2102.06171) in TensorFlow 2.

This is the code for "How to Generate Images - Intro to Deep Learning #14' by Siraj Raval on YouTube

Optimize revenues through pricing algorithm in python - Demand with uniform distribution