srikhetramohanty/Data-Science-Portfolio
This is a repository created in line with my understanding & implementation of the major complex ideas in Machine Learning & Inferential Statistics while working as a data science professional in the industry.
This resource provides comprehensive tutorials and from-scratch implementations of core machine learning and inferential statistics concepts. It offers end-to-end mini-projects demonstrating various data science algorithms, and also includes manual implementations of popular models benchmarked against industry-standard libraries. Data scientists, machine learning engineers, and advanced data analysts can use this to deepen their understanding of how these models work under the hood.
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Use this if you are a data science professional or an aspiring one who wants to validate theoretical knowledge, understand the inner workings of ML models, and apply best practices in real-world scenarios.
Not ideal if you are a beginner looking for an introduction to data science concepts or if you primarily need ready-to-use libraries without delving into the underlying mathematical implementations.
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Jupyter Notebook
License
MIT
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Last pushed
Mar 09, 2022
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