Model-selection Libraries

6 Components & Libraries

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Model-selection Libraries

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get…

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

Yellowbrick is compatible with Python 3.4 or later and also depends on scikit-learn and matplotlib. The simplest way to install Yellowbrick and its dependencies is from PyPI with pip, Python's prefer…

SGX-Full-OrderBook-Tick-Data-Trading-Strategy

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Framework to capture the dynamics of high-frequency limit order books. In this project I used machine learning methods to capture the high-frequency limit order book dynamics and simple trading strat…

State-of-the art Automated Machine Learning python library for Tabular Data

Classifier: Regression: DataPrepare: Simple Models Wrapper: More examples in the folder ./examples: It integrates many popular frameworks: Run

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

TPOT stands for Tree-based Pipeline Optimization Tool. TPOT2 is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. Consider TPOT2 your Data …

Measure and visualize machine learning model performance without the usual boilerplate.

Measure, visualize, and compare machine learning model performance without the usual boilerplate. Breaking API improvements to be expected. Or, for the latest unreleased version:

Related tags

weakly-supervised-learning

natural-language-processing