Data science блоги
scikit-learn-extra. Python module for machine learning that extends scikit-learn. It includes algorithms that are useful but do not satisfy the scikit-learn inclusion criteria, for instance due to their novelty or lower citation number. Документация.
imbalanced-learn. imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-class imbalance. It is compatible with scikit-learn and is part of scikit-learn-contrib projects. Документация.
mimic. Calibration method for binary classification model.
DESlib. A Python library for dynamic classifier and ensemble selection.
tensorflow. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Документация.
keras. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
kubeflow. Machine Learning Toolkit for Kubernetes.
LightGBM. A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. Документация.
hyperopt-sklearn. Hyperopt-based model selection among machine learning algorithms in scikit-learn
ML-From-Scratch. Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
auto-sklearn. Auto-sklearn frees a machine learning user from algorithm selection and hyperparameter tuning. It leverages recent advantages in Bayesian optimization, meta-learning and ensemble construction. Документация.
kaggle-api. Official Kaggle API.
pythons API. List of Python API Wrappers and Libraries.