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A Beginner’s Guide to Structuring Data Science Project’s Workflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Asides from dedication to discovery and exploration, to succeed in a Data Science project, you must understand the process and optimize it to ensure that the results are reliable and the project is easy to follow, maintain and modify where necessary.

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Global Model Interpretability Techniques for Black Box Models

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction There is no mathematical equation for model interpretability. The post Global Model Interpretability Techniques for Black Box Models appeared first on Analytics Vidhya. ‘Interpretability is the.

Modeling 337
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Polish Up your ML model!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Image 1 In this article, we will be discussing various ways through which we can polish up or fine-tune our machine learning model. The post Polish Up your ML model! We will be using the Housing Dataset for understanding the concepts.

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Building tools for enterprise data science

O'Reilly on Data

The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science. In this episode of the Data Show , I spoke with Vitaly Gordon , VP of data science and engineering at Salesforce. Continue reading Building tools for enterprise data science.

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Model Risk Management And the Role of Explainable Models(With Python Code)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. The post Model Risk Management And the Role of Explainable Models(With Python Code) appeared first on Analytics Vidhya. Photo by h heyerlein on Unsplash Introduction Similar to rule-based mathematical.

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Introduction to Linear Predictive Models – Part 2

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Welcome readers to Part 2 of the Linear predictive model series. The post Introduction to Linear Predictive Models – Part 2 appeared first on Analytics Vidhya.

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Building an end-to-end Polynomial Regression Model in R

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Regression analysis is used to solve problems of prediction based on data statistical parameters. In this article, we will look at the use of a polynomial regression model on a simple example using real statistic data.

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