MGrant96's Stars
EbookFoundation/free-programming-books
:books: Freely available programming books
public-apis/public-apis
A collective list of free APIs
practical-tutorials/project-based-learning
Curated list of project-based tutorials
trekhleb/javascript-algorithms
📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings
jlevy/the-art-of-command-line
Master the command line, in one page
ripienaar/free-for-dev
A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
kdn251/interviews
Everything you need to know to get the job.
awesomedata/awesome-public-datasets
A topic-centric list of HQ open datasets.
binhnguyennus/awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
DovAmir/awesome-design-patterns
A curated list of software and architecture related design patterns.
eugeneyan/applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
kuchin/awesome-cto
A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups
terryum/awesome-deep-learning-papers
The most cited deep learning papers
dexteryy/spellbook-of-modern-webdev
A Big Picture, Thesaurus, and Taxonomy of Modern JavaScript Web Development
keon/awesome-nlp
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
oxford-cs-deepnlp-2017/lectures
Oxford Deep NLP 2017 course
kailashahirwar/cheatsheets-ai
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
dibgerge/ml-coursera-python-assignments
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
dair-ai/ML-Notebooks
:fire: Machine Learning Notebooks
cheatsheet1999/FrontEndCollection
Notes for Fullstack Software Engineers. Covers common data structure and algorithms, web concepts, Javascript / TypeScript, React, and more!
indy256/Full-stack-Developer-Interview-Questions-and-Answers
:grey_question:Full-stack developer interview questions and answers
b7leung/MLE-Flashcards
200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.
d0r1h/ML-University
Machine Learning Open Source University
georgearun/Data-Science--Cheat-Sheet
Cheat Sheets
napsternxg/awesome-scholarly-data-analysis
A curated collection of resources on scholarly data analysis ranging from datasets, papers, and code about bibliometrics, citation analysis, and other scholarly commons resources.
aakash1104/Graph-Algorithms
Everything you need to know about graph theory to ace a technical interview :fire:
emrahsariboz/Machine-learning-portfolio
Machine learning portfolio
rickwierenga/MLFundamentals
Notebooks for the "ML from the Fundamentals" series
emrahsariboz/Deep-Learning-Portfolio
Journey of Deep Learning
emrahsariboz/data-science-portfolio
Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.