Anuj Dutt's repositories
Disease-Prediction-from-Symptoms
Disease Prediction based on Symptoms.
Handwritten-Digit-Recognition-using-Deep-Learning
Handwritten Digit Recognition using Machine Learning and Deep Learning
Encrypted-Machine-Learning
Exploration and Projects using Encrypted Machine Learning.
PyTorch-DeepLearning
Deep Learning Tutorials using PyTorch.
LwPosr-PyTorch
Paper Implementation - "LwPosr: Lightweight Efficient Fine Grained Head Pose Estimation"
anujdutt9.github.io
My Blog on ML, DL, NLP, Image Processing and a lot more.
Complete-Placement-Preparation
This repository consists of all the material required for cracking the coding rounds and technical interviews during placements.
Deep-Learning-TF-2.0
ML and DL Projects and Papers Implementations using TF-2.0.
Loads-Of-Logic
Repository with leetcode solutions and dedicated index to prepare for your Meta, Google, Amazon, Microsoft interviews. Feel free to share and contribute to this awesome repository.
OpenAI-API-Examples
Sample Applications built using OpenAI API's.
The-Complete-FAANG-Preparation
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 Interview questions, and Miscellaneous Stuff (Programming MCQs, Puzzles, Aptitude, Reasoning). The Programming languages used for demonstration are C++, Python,
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.
Decentralized-Applications
Decentralized Applications using Solidity on Etherium Blockchain.
faster-pytorch-blog
Outlining techniques for improving the training performance of your PyTorch model without compromising its accuracy
Knowledge-Distillation-Zoo
Pytorch implementation of various Knowledge Distillation (KD) methods.
nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
SqueezeNet-PyTorch
Paper Implementation - "SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size".
TensorFlow-Advanced-Techniques-Specilaization-in-PyTorch
Porting all code examples and assignments in TensorFlow Advanced Specialization to PyTorch.