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abhat222-data-science--cheat-sheet

aics-columbia-s2018

awesome-microservices

A curated list of Microservice Architecture related principles and technologies.

chat-bot-with-yelp-api-and-nlp-capabilities

cheatsheetseries

The OWASP Cheat Sheet Series was created to provide a concise collection of high value information on specific application security topics.

clean-code-python

:bathtub: Clean Code concepts adapted for Python

computer-vision-projects

Canny Edge Detector and Human Detector

ctci-solutions

Python solutions to Cracking the Coding Interview (6th edition)

deep-learning

deep-learning-models

Keras code and weights files for popular deep learning models.

design-resources-for-developers

Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more

extract-data-from-tweeter-and-save-in-azure-sql-using-azure-serverless

Extract Data From Tweeter And Save In Azure SQL Using Azure ServerLess Function

fake-news-detector

gans-awesome-applications

Curated list of awesome GAN applications and demo

how-web-works

What happens behind the scenes when we type www.google.com in a browser?

infovis-spring-19-

interactive-coding-challenges

120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

intro-to-d3

a D3.js tutorial

js_data

Data manipulation and processing in JavaScript

jsdoc

An API documentation generator for JavaScript.

ksw352.github.io

latest-news-classifier

Master in Data Science Final Project

learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

lnav

Log file navigator

mac-cli-tools

My favorite cli tools

machine_learning_nyu

NYU machine learning course

pattern_classification

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

practicalai

📚 A practical approach to learning and using machine learning.

python-learning

r-in-finance

This course, taught by Prof.Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading), and other active portfolio management strategies. The course implements volatility and price forecasting models, asset pricing and factor models, and portfolio optimization. The course applies machine learning techniques, such as backtesting (cross-validation) and parameter regularization (shrinkage).