Rémy Marquis's Projects
:notebook: Source for joelglovier.com. Built with Jekyll and hosted on GitHub Pages.
A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstartes basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.
The projects and materials that accompany the Kotlin Coroutines by Tutorials book
Learn Kubernetes in a Month of Lunches
This repository contains the most common algorithms and data structures written in the Kotlin language with simple and concise code.
Kotlin By Example
Curation of libraries, media, links, and other resources to use Kotlin for data science
Kotlin Design Patterns and Best Practices - Second Edition, published by Packt
A thorough introduction to Kotlin, aimed at developers with a background in Python or other dynamic languages.
A quick guide to Kotlin for developers.
A US keyboard layout expanded with Swiss diacritics
Becoming 1% better at data science everyday
Oxford Deep NLP 2017 course
A complete daily plan for studying to become a machine learning engineer.
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
machine learning and deep learning tutorials, articles and other resources
Plain python implementations of basic machine learning algorithms
Integrate Magisk root and Google Apps (OpenGApps) into WSA (Windows Subsystem for Android)
A curated collection of marketing articles & tools to grow your product.
Minimal is a Jekyll theme for GitHub Pages
Minimalist is a Jekyll theme inspired by the Minimal theme
There are always multiple ways to complete a task in Pandas. A minimal subset of the library is sufficient for almost everything.
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
WIP: Roadmap to becoming a machine learning engineer in 2020
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Preparing for machine learning interviews
https://huyenchip.com/ml-interviews-book/
🛠 MLOps end-to-end guide and tutorial website, using IBM Watson, DVC, CML, Terraform, Github Actions and more.
🎲 A curated list of MLOps projects, tools and resources