Arneish Prateek's starred repositories
project-based-learning
Curated list of project-based tutorials
ohmyzsh
🙃 A delightful community-driven (with 2,300+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python, etc), 140+ themes to spice up your morning, and an auto-update tool so that makes it easy to keep up with the latest updates from the community.
eShopOnContainers
Cross-platform .NET sample microservices and container based application that runs on Linux Windows and macOS. Powered by .NET 7, Docker Containers and Azure Kubernetes Services. Supports Visual Studio, VS for Mac and CLI based environments with Docker CLI, dotnet CLI, VS Code or any other code editor. Moved to https://github.com/dotnet/eShop.
Data-Science--Cheat-Sheet
Cheat Sheets
the-incredible-pytorch
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
LaTeX-Workshop
Boost LaTeX typesetting efficiency with preview, compile, autocomplete, colorize, and more.
azure-docs
Open source documentation of Microsoft Azure
StockSharp
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
aws-solutions-architect-associate-notes
My notes for AWS Solutions Architect Associate.
pykiteconnect
The official Python client library for the Kite Connect trading APIs
kaggle_Microsoft_Malware
code for kaggle competition Microsoft malware classification
deep-learning-map
Map of deep learning and notes from papers.
iitdthesis
Latex template for IITD theses
Parallel-LU-Gaussian-Elimination-with-MPI
Nankai University(NKU) "Introduction to Parallel Programming" course project（南开大学《并行程序设计》课程）
Log-Anomaly-Detection
End-to-end Log Anomaly system for the Nokia Log AD Challenge. :trophy: Winners
subgraph-isomorphism
Resources on subgraph isomorphism
Data-Mining
Data Mining course projects
Ride-Sharing
A repository containing all information related to the ride-sharing paper published in WWW 2019
COL333Assignment1
Code for assignment 1 of Artificial Intelligence course
CUDA_PCA_jacobi
Principal Component Analysis with CUDA implementation of Jacobi method to find eigenvalues and eigenvectors