Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
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Updated
Feb 5, 2025 - Python
Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
Solution to kaggle competition OTTO – Multi-Objective Recommender System: https://www.kaggle.com/competitions/otto-recommender-system
Scaling ML models with Taipy and Dask
A Dask native implementation of 'Term Frequency Inverse Document Frequency' for dask-ml and scikit-learn
A Parallel segmentation algorithm of a flowers dataset using Dask.
Sentiment analysis on hotel reviews, using MongoDB, applying Dask parallel programming, comparing Recurrent and Convolutional neural networks and visualizating with Dash.
one-stop destination for all machine learning and artificial intelligence library and algorithms
BETA: Real-time inference from scalable machine learning in Python
Word2vec for large corpus for Bangle
Preprocessing and predicting big data
In this repo, I build a LogisticRegression prediction model with Dask and PySpark and initialize an AWS EMR cluster to run the entire pipeline.
pybear is a Python computing library that augments data analytics functionality found in the popular numpy, scikit-learn, dask, and dask_ml libraries.
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