parameter-tuning

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

(Deprecated) Scikit-learn integration package for Apache Spark

LAMA - automatic model creation framework

Automated modeling and machine learning framework FEDOT

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

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

Hyperparameter optimization in Julia.

Workflow engine for exploration of simulation models using high throughput computing

⚡ Fast Concurrent / Parallel Sorting in Go

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

Alchemy Cat —— 🔥Config System for SOTA

Purely functional genetic algorithms for multi-objective optimisation

Framework of intelligent optimization methods iOpt

An abstraction layer for parameter tuning

A Python Toolkit for Managing a Large Number of Experiments

Globally Safe Model-free Exploration of Dynamical Systems

Understand the relationships between various features in relation with the sale price of a house using exploratory data analysis and statistical analysis. Applied ML algorithms such as Multiple Linear Regression, Ridge Regression and Lasso Regression in combination with cross validation. Performed parameter tuning, compared the test scores and suggested a best model to predict the final sale price of a house. Seaborn is used to plot graphs and scikit learn package is used for statistical analysis.

A CLI-based tuner that runs multi-objective optimization on your ESPminer.

Learning simulation parameters from experimental data, from the micro to the macro, from laptops to clusters.