scikit-learn

[UNMAINTAINED] Automated machine learning for analytics & production

MLeap: Deploy ML Pipelines to Production

Machine learning Guide. Learn all about Machine Learning Tools, Libraries, Frameworks, Large Language Models (LLMs), and Training Models.

skops is a Python library helping you share your scikit-learn based models and put them in production

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs

Amazon SageMaker Local Mode Examples

Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news article sentiment collected using APIs and web scraping.

Conversational text Analysis using various NLP techniques

Interpret text data with LLMs (sklearn compatible).

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and Topic Models.

Hands-on MLOps projects to explore and learn the practical aspects of machine learning engineering for production.

Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.

Serve scikit-learn, XGBoost, TensorFlow, and PyTorch models with AWS Lambda container images support.

🔍 AI-powered diagnosis for Scikit-learn models: Detect overfitting, data leakage, class imbalance & more with LLM-generated insights

A collection of AI/ML articles, guides and projects.

Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.

Tree prompting: easy-to-use scikit-learn interface for improved prompting.

The Practical Machine Learning Course focuses on equipping learners with the essential skills and tools needed to apply machine learning techniques in real-world scenarios.

Empowering Data Driven insights through hands-on projects, SQL challenges and practical tools.

Content based recommender system for books using NLP.