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  1. Mathematical introduction to machine learning algorithms


Introduction of one of the most wide-used categories of models-supervised learning. Detailed descriptions of the methods, application, and characteristics of several models. A coding example also provided for the audience to be familiar with how to prepare data and construct a model using sklearn and pandas.

RMDS Lab is a pioneer in developing data science and AI ecosystems, and in offering extensive assistance for data science with its unique RM4Es framework, ResearchMap, and ecosystem approach. We exist to empower our clients worldwide to achieve successful, data-driven results. With resources and tools in our robust scientific community, we have the capability to advance your project impact through data impact consultation and AI-powered services that evaluates your needs, deploys the necessary solutions, and maximize the effectiveness.

RMDS expands your company's reach to find new technologies and resources with the goal of reshaping how commercial clients, researchers and data scientists with industry experience work together to develop high-impact data science solutions.

We have a long-standing Ecosystem of data scientists, engineers and subject matter experts, eager to be your trusted partner, enhance your research, increase the success rate of your work, and leverage the power of analytics. Each of our consultant teams has experience delivering and commercializing E2E data science solutions and software.

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Source: Introduction to ML Models in Data Science PDF document


Introduction to ML Models in Data Science

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File Type: PDF (pdf)

File Size: 4.8 MB

Number of Pages: 23

Related Topic(s): Machine Learning Data Science

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Initial upload date (first version): May 6, 2021
Most recent version published: May 7, 2021

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