Repository Index

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

• python
• machine-learning
• deep-learning
• data-science

Open standard for machine learning interoperability

• deep-learning
• deep-neural-networks
• neural-network
• onnx

Fast and Accurate ML in 3 Lines of Code

• automl
• machine-learning
• data-science
• deep-learning

Open Machine Learning Course

• machine-learning
• data-analysis
• data-science
• pandas

A unified framework for machine learning with time series

• time-series
• machine-learning
• scikit-learn
• time-series-classification

Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

• data-science
• python
• machine-learning
• pycaret

Automated Machine Learning with scikit-learn

• automl
• scikit-learn
• automated-machine-learning
• hyperparameter-optimization

An open source python library for automated feature engineering

• feature-engineering
• machine-learning
• data-science
• automated-machine-learning

Visual analysis and diagnostic tools to facilitate machine learning model selection.

• machine-learning
• visual-analysis
• model-selection
• visualization

Seamlessly integrate LLMs into scikit-learn.

• chatgpt
• deep-learning
• llm
• machine-learning

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

• machine-learning
• scikit-learn
• statistical-learning
• xgboost

An intuitive library to add plotting functionality to scikit-learn objects.

• scikit-learn
• visualization
• machine-learning
• data-science

A modular active learning framework for Python

• scikit-learn
• machine-learning
• python
• active-learning

Feature engineering and selection open-source Python library compatible with sklearn.

• machine-learning
• data-science
• python
• scikit-learn

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

• visualization
• python3
• python
• xgboost

Genetic Programming in Python, with a scikit-learn inspired API

• genetic-programming
• machine-learning
• python
• scikit-learn

Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models

• forecasting
• scikit-learn
• machine-learning
• python

Metric learning algorithms in Python

• python
• metric-learning
• scikit-learn
• machine-learning

Extra blocks for scikit-learn pipelines.

• scikit-learn
• machine-learning
• common-sense

Transpile trained scikit-learn estimators and transformers to C, C#, Go, Java, JavaScript, PHP and Ruby.

• machine-learning
• data-science
• scikit-learn
• sklearn

PySpark + Scikit-learn = Sparkit-learn

• scikit-learn
• apache-spark
• machine-learning
• distributed-computing

A scikit-learn based module for multi-label et. al. classification

• classification
• scikit
• scikit-learn
• multi-label

Combines the ease of use of scikit-learn with the power of Theano/Lasagne

• scikit-learn
• lasagne
• deep-learning
• machine-learning

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

• pipeline
• pipeline-framework
• machine-learning
• deep-learning