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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TsfreshAutomatic extraction of relevant features from time series:
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Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
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TsfelAn intuitive library to extract features from time series
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PbaEfficient Learning of Augmentation Policy Schedules
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Datasist A Python library for easy data analysis, visualization, exploration and modeling
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Data ScienceCollection of useful data science topics along with code and articles
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msdaLibrary for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
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NniAn open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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NlpaugData augmentation for NLP
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Awesome Feature EngineeringA curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
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Feature SelectionFeatures selector based on the self selected-algorithm, loss function and validation method
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FeatexpFeature exploration for supervised learning
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Python TrainingPython training for business analysts and traders
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Fecon235Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
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NlpythonThis repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
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PycaretAn open-source, low-code machine learning library in Python
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Open source demosA collection of demos showcasing automated feature engineering and machine learning in diverse use cases
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Mckinsey Smartcities Traffic PredictionAdventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge
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H1stThe AI Application Platform We All Need. Human AND Machine Intelligence. Based on experience building AI solutions at Panasonic: robotics predictive maintenance, cold-chain energy optimization, Gigafactory battery mfg, avionics, automotive cybersecurity, and more.
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Scipy con 2019Tutorial Sessions for SciPy Con 2019
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Machine Learning Workflow With PythonThis is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
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BlurrData transformations for the ML era
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LearnpythonforresearchThis repository provides everything you need to get started with Python for (social science) research.
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AI4Waterframework for developing machine (and deep) learning models for structured data
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tsflexFlexible time series feature extraction & processing
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machine learning courseArtificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)
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AutoTSAutomated Time Series Forecasting
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FmixOfficial implementation of 'FMix: Enhancing Mixed Sample Data Augmentation'
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mtss-ganMTSS-GAN: Multivariate Time Series Simulation with Generative Adversarial Networks (by @firmai)
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50-days-of-Statistics-for-Data-ScienceThis repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.
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AutoTabularAutomatic machine learning for tabular data. ⚡🔥⚡
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pybacenThis library was developed for economic analysis in the Brazilian scenario (Investments, micro and macroeconomic indicators)
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autoencoders tensorflowAutomatic feature engineering using deep learning and Bayesian inference using TensorFlow.
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featurewizUse advanced feature engineering strategies and select best features from your data set with a single line of code.
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AtspyAtsPy: Automated Time Series Models in Python (by @firmai)
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feature engineFeature engineering package with sklearn like functionality
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fastknnFast k-Nearest Neighbors Classifier for Large Datasets
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mistqlA miniature lisp-like language for querying JSON-like structures. Tuned for clientside ML feature extraction.
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Course NlpA Code-First Introduction to NLP course
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FacetHuman-explainable AI.
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GophernotesThe Go kernel for Jupyter notebooks and nteract.
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Ml sagemaker studiesCase studies, examples, and exercises for learning to deploy ML models using AWS SageMaker.
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okamaInvestment portfolio and stocks analyzing tools for Python with free historical data
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Python Is CoolCool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
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