eugeneyan/applyingml

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Created over 3 years ago
Updated over 1 year ago

eugeneyan/applyingml

eugeneyan

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📌 Papers, guides, and mentor interviews on applying machine learning for ApplyingML.com—the ghost knowledge of machine learning.

📌 applyingml

Repository for applyingml.com containing papers, resources, and mentor interviews on how to apply machine learning.

Have questions? Reach out to @eugeneyan.

Quickstart

# Install Gatsby (https://www.gatsbyjs.com/get-started/)
npm init gatsby

# Clone this repository
git clone https://github.com/eugeneyan/applyingml.git
cd applyingml

# Develop on local (http://localhost:8000)
gatsby develop

Contributing

Mentor interviews

Make a copy of the interview template.
Rename it to your <firstname-lastname>.mdx.
Fill in your responses.
Make a pull request with your mdx.

Suggestions and fixes

Make a pull request with your proposed changes.

Other details

Bootstrapped with Gatsby's hello-world starter
Built and deployed on push to main via Gatsby Publish

P.S. This is my first project with JavaScript and React. Suggestions for improvement, feedback on how I'm using JS/Gatsby/React wrong, and code reviews welcome!

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

open-llms

📋 A list of open LLMs available for commercial use.

ml-surveys

📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.

ml-design-docs

📝 Design doc template & examples for machine learning systems (requirements, methodology, implementation, etc.)

1-on-1s

🌱 1-on-1 questions and resources from my time as a manager.

testing-ml

🔍 Minimal examples of machine learning tests for implementation, behaviour, and performance.

obsidian-copilot

🤖 A prototype assistant for writing and thinking

papermill-mlflow

🧪 Simple data science experimentation & tracking with jupyter, papermill, and mlflow.

Jupyter Notebook

python-collab-template

🛠 Python project template with unit tests, code coverage, linting, type checking, Makefile wrapper, and GitHub Actions.

recsys-nlp-graph

🛒 Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.

llm-paper-notes

Notes from the Latent Space paper club. Follow along or start your own!

fastapi-html

Sample repository demonstrating how to use FastAPI to serve HTML web apps.

eugeneyan

poc-docker-template

Simple template showing how to set up docker for reproducible data science with Jupyter notebooks.

Jupyter Notebook

text-to-image

Jupyter Notebook

nocode-ml

😝 End-to-end machine learning; "no code" required!

discord-llm

Experimenting with LLMs to Research, Reflect, and Plan (LLM assistants, retrieval, and Discord integration)

Jupyter Notebook

learning-typescript

design-patterns

deep-rl

Repository for deep reinforcement learning with OpenAI

testing-pipelines

kaggle_springleaf

Code for Kaggle Springleaf Email Prediction Challenge

Computational-Thinking-and-Data-Science

edX: Introduction to Computational Thinking and Data Science (Oct 2014)

ama

Ask Me Anything

Mining-Massive-Datasets

Coursera: Mining Massive Datasets (Sep 2014)

Time-Series-Analysis

Simple forecasting with Regression Model

raspberry-llm

Calling LLM APIs on a Raspberry Pi for lulz

Statistical-Inference

This repository contains the lab assignments for the facilitation of John Hopkins University' Coursera MOOC on Statistical Inference.

kaggle_titanic

Code for Kaggle Titanic Challenge (and other learning)

Statistical-Learning

Stanford OpenX: Introduction to Statistical Learning

Data-Analysis-and-Statistical-Inference-Project

Coursera: Data Analysis & Statistical Inference Project (Feb 2014)

neural_networks_and_deep_learning

Twitter-SMA

Twitter Streaming and Analysis with Python and R

scratch

Jupyter Notebook

Getting-and-Cleaning-Data

Coursera: Getting and Cleaning Data (May 2014)

Computer-Science-and-Programming-In-Python

edX: Introduction to Computer Science and Programming in Python (July 2014)

Misc

datagene

Jupyter Notebook

Interactive-Programming-in-Python

Coursera: Interactive Programming in Python (Apr 2014)

R-Programming

Coursera: R Programming (May 2014)

Visualizations

Random Visualizations

json-to-utterances

Jupyter Notebook

DKSG-HOME

Sharing my R script used in the DKSG DataLearn for home

eugeneyan-comments

kaggle_otto

Code for Kaggle Otto Production Classification Challenge

Demand-Forecasting

Prototyping various forecasting techniques

Machine-Learning

Coursera: Machine Learning (Aug 2014)