Here lies the resources and topics necessary for the role of Data Scientist and Machine Learning
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Tools
335 results
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly
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INCEpTION provides a semantic annotation platform offering intelligent annotation assistance and knowledge management.
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List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dy
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DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing la
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Open-source PyTorch tool that traces live training signals back to the data samples causing them. Pause the training to
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Turns Data and AI algorithms into production-ready web applications in no time.
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An orchestration platform for the development, production, and observation of data assets.
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Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create dat
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Source code accompanying book: Data Science on the Google Cloud Platform, Valliappa Lakshmanan, O'Reilly 2017
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Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI a
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R programming tips for data cleaning, data visualisation, statistical modelling and machine learning
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Visualise your Kedro data and machine-learning pipelines and track your experiments.
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Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]
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A Full Stack ML (Machine Learning) Roadmap involves learning the necessary skills and technologies to become proficient
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