eugeneyan/Computer-Science-and-Programming-In-Python

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eugeneyan/Computer-Science-and-Programming-In-Python

eugeneyan

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

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

applyingml

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

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)

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)