MlboxMLBox is a powerful Automated Machine Learning python library.
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LightautomlLAMA - automatic model creation framework
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MachinelearningcourseA collection of notebooks of my Machine Learning class written in python 3
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Eli5A library for debugging/inspecting machine learning classifiers and explaining their predictions
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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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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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LightgbmA fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
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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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AirbyteAirbyte is an open-source EL(T) platform that helps you replicate your data in your warehouses, lakes and databases.
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BatchflowBatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
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Pytorch UnetPyTorch implementation of the U-Net for image semantic segmentation with high quality images
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Bodywork CoreDeploy machine learning projects developed in Python, to Kubernetes. Accelerated MLOps 🚀
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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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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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Pytorch ToolbeltPyTorch extensions for fast R&D prototyping and Kaggle farming
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PipelinexPipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
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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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Allstate capstoneAllstate Kaggle Competition ML Capstone Project
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Ds bowl 2018Kaggle Data Science Bowl 2018
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docker-kaggle-ko머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.
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Painters🎨 Winning solution for the Painter by Numbers competition on Kaggle.
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autogbt-altAn experimental Python package that reimplements AutoGBT using LightGBM and Optuna.
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kaggle-plasticcSolution to Kaggle's PLAsTiCC Astronomical Classification Competition
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kaggle-quora-question-pairsMy solution to Kaggle Quora Question Pairs competition (Top 2%, Private LB log loss 0.13497).
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fabricUrban change model designed to identify changes across 2 timestamps
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pixel-decoderA tool for running deep learning algorithms for semantic segmentation with satellite imagery
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SteppyLightweight, Python library for fast and reproducible experimentation 🔬
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Auto ml[UNMAINTAINED] Automated machine learning for analytics & production
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ChefboostA Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python
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Kaggle-Competition-SberbankTop 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
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HumanOrRobota solution for competition of kaggle `Human or Robot`
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