gargankush

AMLSim

The AMLSim project is intended to provide a multi-agent based simulator that generates a series of banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing your machine learning models and graph algorithms. We welcome you to enhance this effort since data set is critical to advance our detection capabilities of money laundering activities .

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

AWS_Learning

Cloud-based-stock-selection-app

CSE6242 - Data and Visual Analytics group project

Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

crawl-reuters

A simple Scrapy script for crawling Reuters news articles (Python 3)

Data-Science--Cheat-Sheet

Cheat Sheets

Data-Science-Free

Free Resources For Data Science created by Shubham Kumar

marketdata_yfinance

Market data pull from yfinance API

SP500_Stock_List

Repository to pull S&P 500 stock list from wikipedia

gargankush/marketdata_yfinance

Market data pull from yfinance API

gargankush/SP500_Stock_List

Repository to pull S&P 500 stock list from wikipedia

gargankush/AMLSim

The AMLSim project is intended to provide a multi-agent based simulator that generates a series of banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing your machine learning models and graph algorithms. We welcome you to enhance this effort since data set is critical to advance our detection capabilities of money laundering activities .

gargankush/AWS_Learning

gargankush/Cloud-based-stock-selection-app

CSE6242 - Data and Visual Analytics group project

gargankush/Complete-Python-3-Bootcamp

Course Files for Complete Python 3 Bootcamp Course on Udemy

gargankush/Data-Science--Cheat-Sheet

Cheat Sheets

gargankush/Data-Science-Free

Free Resources For Data Science created by Shubham Kumar

gargankush/deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

gargankush/financials_scrape

This code will allow you to pull the last 5 years of financials from any stock on Reteurs and perform fundamental analysis based on the data.

gargankush/GetCards

Notebook to download machine learning flashcards

gargankush/github-slideshow

A robot powered training repository :robot:

gargankush/gitProject

gargankush/Listening-to-Chaotic-Whishpers--Code

gargankush/machine-learning-for-trading

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

gargankush/marketData_FMP

Sourcing market data from financial modelling prep API

gargankush/marketdata_YAHOO_FIN

Source market data from YAHOO Finance api YAHOO_FIN

gargankush/news-crawler

A news crawler for BBC News, Reuters and New York Times.

gargankush/NewsReader

Prints headlines from Google, Reuters, CNN, Fox, ABC, Forbes, Yahoo, and BBC using Dashblock.

gargankush/NLP_Learning

gargankush/Path-to-Data-Scientist

Learning path to become Data Scientist

gargankush/practicalAI

📚 A practical approach to machine learning.

gargankush/Python

All Algorithms implemented in Python

gargankush/PythonDataScienceHandbook

Python Data Science Handbook: full text in Jupyter Notebooks

gargankush/ReutersParser

gargankush/spain

Implementation of a Neural Network to classify text with Python and Keras

gargankush/tensorflow

An Open Source Machine Learning Framework for Everyone

gargankush/Twitter-Sentiment-Analysis-Classical-Approach-VS-Deep-Learning

This project's aim, is to explore the world of Natural Language Processing (NLP) by building what is known as a Sentiment Analysis Model. We will be implementing and comparing both a Naïve Bayes and a Deep Learning LSTM model.

gargankush/web-scraping

Python detailed web scraping tutorials for dummies with financial data crawlers on CME (both futures and options), CFTC, LME, SHFE and news data crawlers on BBC, Wall Street Journal, Al Jazeera, Reuters, Financial Times, Bloomberg, CNN, Fortune, The Economist

gargankush/yao-lab.github.io