cvredenburgh

trinity-ie

Information extraction pipeline containing coreference resolution, named entity linking, and relationship extraction

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

MLOpsLearning

This repository provides some basic training materials for data scientists

PaLM-rlhf-pytorch

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

char-rnn

Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch

automatic_prompt_engineer

SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

Data-Science-Projects

Collection of data science projects in Python

best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

Data-Science-Interview-Questions-Answers

Curated list of data science interview questions and answers

Data-Science-Interview-Resources

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

SymbolicPlanners.jl

Symbolic planners for problems and domains specified in PDDL.

gym-cooking

🏆 gym-cooking: Code for "Too many cooks: Bayesian inference for coordinating multi-agent collaboration", Winner of the CogSci 2020 Computational Modeling Prize in High Cognition, and a NeurIPS 2020 CoopAI Workshop Best Paper.

DS-Take-Home

My solution to the book A Collection of Data Science Take-Home Challenges

Amazon-use-cases

lag-llama

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

scalecast

The practitioner's forecasting library

dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

causal-inference-tutorial

Repository with code and slides for a tutorial on causal inference.

MLQuestions

Machine Learning and Computer Vision Engineer - Technical Interview Questions

Machine-Learning-Interviews

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

machine-learning-interview

Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.

multi-armed-bandit

freeCodeCamp

freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

coding-interview-university

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

the-book-of-secret-knowledge

A collection of inspiring lists, manuals, cheatsheets, blogs, hacks, one-liners, cli/web tools and more.

llm-app-stack

bayesian_mmm

Code for the article Modeling Marketing Mix using PyMC3

Deedy-Resume

A one page , two asymmetric column resume template in XeTeX that caters to an undergraduate Computer Science student

pymc-marketing

Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.