jpv-costa's Stars
microsoft/ML-For-Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
LAION-AI/Open-Assistant
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
microsoft/Data-Science-For-Beginners
10 Weeks, 20 Lessons, Data Science for All!
ydataai/ydata-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
twitter/the-algorithm-ml
Source code for Twitter's Recommendation Algorithm
khangich/machine-learning-interview
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
alteryx/featuretools
An open source python library for automated feature engineering
evidentlyai/evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
alirezadir/Production-Level-Deep-Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
Giskard-AI/giskard
🐢 Open-Source Evaluation & Testing for AI & LLM systems
nalepae/pandarallel
A simple and efficient tool to parallelize Pandas operations on all available CPUs
GokuMohandas/mlops-course
Learn how to design, develop, deploy and iterate on production-grade ML applications.
whylabs/whylogs
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
chiphuyen/dmls-book
Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)
aws/sagemaker-python-sdk
A library for training and deploying machine learning models on Amazon SageMaker
Trusted-AI/AIX360
Interpretability and explainability of data and machine learning models
wangyongjie-ntu/Awesome-explainable-AI
A collection of research materials on explainable AI/ML
mahmoudparsian/pyspark-tutorial
PySpark-Tutorial provides basic algorithms using PySpark
coding-parrot/Low-Level-Design
Useful Resources for Low Level System Design
salesforce/OmniXAI
OmniXAI: A Library for eXplainable AI
Ekeany/Boruta-Shap
A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
limexp/xgbfir
XGBoost Feature Interactions Reshaped
mahmoudparsian/data-algorithms-with-spark
O'Reilly Book: [Data Algorithms with Spark] by Mahmoud Parsian
eugeneyan/recsys-nlp-graph
🛒 Simple recommender with matrix factorization, graph, and NLP. Beating the regular collaborative filtering baseline.
outerbounds/dsbook
Code samples for the Effective Data Science Infrastructure book
andfanilo/pyspark-tutorial
Jupyter notebooks for pyspark tutorials given at University
logicai-io/recsys2019
mahmoudparsian/pyspark-algorithms
PySpark Algorithms Book: https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2
estamos/Neural-Network-Design-Solutions-Manual
📑 Solution manual for the text book Neural Network Design 2nd Edition by Martin T. Hagan, Howard B. Demuth, Mark Hudson Beale, and Orlando De Jesus
ooanishoo/log-me
Log Me is a workout tracker application built using flutter. 🏋🏻♀️