MlboxMLBox is a powerful Automated Machine Learning python library.
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Kaggle CompetitionsThere are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
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Data Science CompetitionsGoal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).
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LightautomlLAMA - automatic model creation framework
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DatascicompA collection of popular Data Science Challenges/Competitions || Countdown timers to keep track of the entry deadlines.
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Data Science ProjectsDataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
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TargetsFunction-oriented Make-like declarative workflows for R
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Data Science Ipython NotebooksData science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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Machinejs[UNMAINTAINED] Automated machine learning- just give it a data file! Check out the production-ready version of this project at ClimbsRocks/auto_ml
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Kaggle Homedepot3rd Place Solution for HomeDepot Product Search Results Relevance Competition on Kaggle.
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Pytorch ToolbeltPyTorch extensions for fast R&D prototyping and Kaggle farming
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Mlj.jlA Julia machine learning framework
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Ds Take HomeMy solution to the book A Collection of Data Science Take-Home Challenges
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Data Science Bowl 2018End-to-end one-class instance segmentation based on U-Net architecture for Data Science Bowl 2018 in Kaggle
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Bodywork CoreDeploy machine learning projects developed in Python, to Kubernetes. Accelerated MLOps 🚀
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SetlA simple Spark-powered ETL framework that just works 🍺
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Amazon Forest Computer VisionAmazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks
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ServingA flexible, high-performance carrier for machine learning models(『飞桨』服务化部署框架)
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D2l VnMột cuốn sách tương tác về học sâu có mã nguồn, toán và thảo luận. Đề cập đến nhiều framework phổ biến (TensorFlow, Pytorch & MXNet) và được sử dụng tại 175 trường Đại học.
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PdpipeEasy pipelines for pandas DataFrames.
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Vehicle counting tensorflow🚘 "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
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Steppy ToolkitCurated set of transformers that make your work with steppy faster and more effective 🔭
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DrakeAn R-focused pipeline toolkit for reproducibility and high-performance computing
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MachinelearningcourseA collection of notebooks of my Machine Learning class written in python 3
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Painters🎨 Winning solution for the Painter by Numbers competition on Kaggle.
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Allstate capstoneAllstate Kaggle Competition ML Capstone Project
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D2l EnInteractive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.
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BlurrData transformations for the ML era
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Dev PracticePractice your skills with these ideas.
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MlA high-level machine learning and deep learning library for the PHP language.
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Pathwar☠️ The Pathwar Project ☠️
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Chain.jlA Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
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Kaggle HousepricesKaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-is-pca-lb-0-11421-top-4
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Tennis Crystal BallUltimate Tennis Statistics and Tennis Crystal Ball - Tennis Big Data Analysis and Prediction
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SkproSupervised domain-agnostic prediction framework for probabilistic modelling
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SteppyLightweight, Python library for fast and reproducible experimentation 🔬
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HumanOrRobota solution for competition of kaggle `Human or Robot`
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kaggler🏁 API client for Kaggle
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Drake ExamplesExample workflows for the drake R package
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SegmentationTensorflow implementation : U-net and FCN with global convolution
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