{"repo":"gershonc/octopus-ml","free":true,"listed":false,"github":"https://github.com/gershonc/octopus-ml","clone":"git clone https://github.com/gershonc/octopus-ml.git","description":"A collection of handy ML and data visualization and validation tools. Go ahead and train, evaluate and validate your ML models and data with minimal effort.","language":"Jupyter Notebook","stars":23,"topics":["machine-learning","data-science","data","data-visualization","ai","data-validation","data-integrity","cross-validation","eda","classification"],"license":"MIT","category":"machine-learning","readme_excerpt":"Octopus-ML Set of handy ML and data tools - starting from data exploration, visualization, pre-processing, hyper parameter tuning, modeling and all the way to final ML model evaluation Check out the octopus-ml demo notebook on Colab Installation The module can be easily installed with pip: This module depends on Scikit-learn , NumPy , Pandas , TQDM , lightGBM as defualt classifier. Optionally you can get also some nice visualisations if you have Seaborn installed. Usage The module contains ML and Data related methods: Selected visualizations:","default_branch":null,"files":null,"tree":[],"storefront":"/r/gershonc","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/gershonc/octopus-ml/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}