akshaybahadur21

akshaybahadur21's Stars

• resume/resume.github.com

  Resumes generated using the GitHub informations

  Language:JavaScript62k3451191.4k

• zziz/pwc

  This repository is no longer maintained.

  15.4k1.2k242.5k

• NVIDIA/vid2vid

  Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.

  Language:Python8.6k2461681.2k

• dragen1860/TensorFlow-2.x-Tutorials

  TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。

  Language:Jupyter Notebook6.4k227382.2k

• udacity/deep-reinforcement-learning

  Repo for the Deep Reinforcement Learning Nanodegree program

  Language:Jupyter Notebook4.9k179352.3k

• keras-team/keras-tuner

  A Hyperparameter Tuning Library for Keras

  Language:Python2.9k63489397

• WillKoehrsen/feature-selector

  Feature selector is a tool for dimensionality reduction of machine learning datasets

  Language:Jupyter Notebook2.2k9751769

• artix41/awesome-transfer-learning

  Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)

  1.7k949301

• maxpumperla/elephas

  Distributed Deep learning with Keras & Spark

  Language:Python1.6k102159310

• philipperemy/keract

  Layers Outputs and Gradients in Keras. Made easy.

  Language:Python1k3388186

• tensorflow/neural-structured-learning

  Training neural models with structured signals.

  Language:Python9854869190

• sourcerer-io/hall-of-fame

  :trophy: Show some love to your contributors! A widget for your repo README. Visual and clean. Refreshes every hour.

  Language:Python947192490

• karpathy/paper-notes

  Random notes on papers, likely a short-term repo.

  669113482

• jbarroso/clean-code

  Notes on the book Clean Code - A Handbook of Agile Software Craftsmanship by Robert C. Martin

  615251173

• akshaybahadur21/Emojinator

  A simple emoji classifier for humans. 🖖

  Language:Python5013327190

• buomsoo-kim/Easy-deep-learning-with-Keras

  Keras tutorial for beginners (using TF backend)

  Language:Jupyter Notebook410160189

• upul/Behavioral-Cloning

  Third Project of the Udacity Self-Driving Car Nanodegree Program

  Language:Python234265101

• facebookresearch/multigrain

  Code for "MultiGrain: a unified image embedding for classes and instances"

  Language:Python231171138

• Santara/ML-MOOC-NPTEL

  This repository contains the Tutorials for the NPTEL MOOC on Machine Learning.

  Language:Jupyter Notebook196363239

• AakashKumarNain/AugMix_TF2

  TF2.0 port for Augmix paper

  Language:Python798111

• dipanjanS/nlp_workshop_dhs18

  Contains code and presentation for our full day workshop, 'Getting Started with Natural Language Processing'. This is created for the purpose of being presented in Analytics Vidhya's DataHack Summit 2018. Authors: Dipanjan Sarkar & Raghav Bali

  Language:Jupyter Notebook6512054

• raghavpatnecha/Hello-Morse-OpenCV

  Morse Code detection with eyes using Computer Vision

  Language:Python555124

• FavioVazquez/ODSC_India_2018

  My presentation at ODSC India 2018 about Deep Learning with Apache Spark

  Language:Jupyter Notebook27608

• ariG23498/GrokkingDeepLearning

  This repository will contain my take on Andrew Trask's book GrokkingDeepLearning.

  Language:Jupyter Notebook131

• toelt-llc/NOTES-TensorFlow20-Notes

  TensorFlow 2.0 Various notes and tutorials

  Language:Jupyter Notebook13204

• anandbikas/coding

  DataStructures, Algorithms and Java coding

  Language:Java11206

• devashishnyati/entity-recognition-problem

  Language:Jupyter Notebook54

• shoreyarchit/Black-Friday-Sales-Analysis

  We all eagerly wait for Black Friday sales and plan ahead in order to make most out of it. Similar is the objective of a retail outlet on Black Friday. They also aspire to bring the best out of this day. The major objective of a store is to maximize the revenue on this day, by selling off a large proportion of their unsold inventory. The main challenge to achieve this objective is “What optimal prices should the store set to capture demand that maximizes revenue?” The problem we solve would help the business to get the predicted Purchase amount (or Willingness to Pay) for each product for each user. They can use this then to set optimal prices on the product (using Multinomial Model for Price Optimization or others). So, when we find Black Friday Sales Analysis data on Kaggle, it highly motivated our team to work for this interesting real-world problem for ABC Retail Store.

  Language:R50

• akshata-bhat/programs_cpp

  My learning in C++

  Language:C++41

• devashishnyati/devashishnyati.github.io

  Language:CSS21