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100-days-of-ml-code

100 Days of ML Coding

2015

Public material for CS109

algorithms

Minimal examples of data structures and algorithms in Python

appium

:iphone: Automation for iOS, Android, and Windows Apps.

articles

This repo contains all the articles written by me, in markdown and also all of their example source code. Mirrored from: https://gitlab.com/hmajid2301/articles

awesome-algorithms

A curated list of awesome places to learn and/or practice algorithms.

awesome-ethical-hacking-resources

🔗 All the resources I could find for learning Ethical Hacking and Penetration Testing.

awesome-javascript

🐢 A collection of awesome browser-side JavaScript libraries, resources and shiny things.

bitcoin

Bitcoin Core integration/staging tree

bitcoin-reading-list

a reading list for learning to program Bitcoin transactions

c-plus-plus

All Algorithms implemented in C++

clmystery

Command Line Murder Mystery

coding-interview-university

A complete computer science study plan to become a software engineer.

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

coursera_capstone

coursera_capstone-1

Capstone project from IBM data science professional certificate

cs50-webdevwithpython-javascript-lecture1

data-science

:bar_chart: Path to a free self-taught education in Data Science!

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data-scientist-roadmap

Toturial coming with "data science roadmap" graphe.

developer-roadmap

Roadmap to becoming a web developer in 2020

docs

en.javascript.info

Modern JavaScript Tutorial

eproject-festivals.com-website

export_import_vn

flask

The Python micro framework for building web applications.

git-and-github

An introduction to git.

go

Algorithms Implemented in GoLang

go-ipfs

IPFS implementation in Go

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.