Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
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Updated
May 18, 2024 - Python
Framework for computing Machine Learning algorithms in Python using Dask and RAPIDS AI.
Classification of volumetric data attacks on network infrastructure using a CNN and LSTM network with the assistance of Dask framework
one-stop destination for all machine learning and artificial intelligence library and algorithms
Preprocessing and predicting big data
A Dask native implementation of 'Term Frequency Inverse Document Frequency' for dask-ml and scikit-learn
Scaling ML models with Taipy and Dask
Fraud detection ML pipeline and serving POC using Dask and hopeit.engine. Project created with nbdev: https://www.fast.ai/2019/12/02/nbdev/
Solution to kaggle competition OTTO – Multi-Objective Recommender System: https://www.kaggle.com/competitions/otto-recommender-system
Adds partial fit method to sklearn's forest estimators to allow incremental training without being limited to a linear model. Works with Dask-ml's Incremental.
Build ColumnTransformers (Scikit or DaskML) for feature transformation by specifying configs.
The following project shows and compares machine learning between Pandas DataFrames and Dask Dataframes.
Sentiment analysis on hotel reviews, using MongoDB, applying Dask parallel programming, comparing Recurrent and Convolutional neural networks and visualizating with Dash.
Dask tutorial;Dask汉化教程
Saturn Cloud workshop on using LightGBM with Dask
Rapidsai_Machine_learnring_on_GPU
Dask-parallelized project, contrasting GaussianNB and LightGBM models for EMNIST handwritten character classification.
In this repo, I build a LogisticRegression prediction model with Dask and PySpark and initialize an AWS EMR cluster to run the entire pipeline.
Word2vec for large corpus for Bangle
A Parallel segmentation algorithm of a flowers dataset using Dask.
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