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The Science of T20 Cricket: Decoding Player Performance with Predictive Modeling

Analytics Vidhya

With franchise leagues like IPL and BBL, teams rely on statistical models and tools for competitive edge. This article explores how data analytics optimizes strategies by leveraging player performances and opposition weaknesses. Python programming predicts player performances, aiding team selections and game tactics.

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Machine Learning Paradigms with Example

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data. Source: [link] For […].

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Bivariate Feature Analysis in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Feature analysis is an important step in building any predictive model. In this article, we will look into a very simple feature analysis technique that can be used in cases such as […].

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Quick Guide to Evaluation Metrics for Supervised and Unsupervised Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Machine learning is about building a predictive model using historical data. The post Quick Guide to Evaluation Metrics for Supervised and Unsupervised Machine Learning appeared first on Analytics Vidhya.

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STANDARDIZED VS UNSTANDARDIZED REGRESSION COEFFICIENT

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon. Introduction Some time back, I was making the predictive model. The post STANDARDIZED VS UNSTANDARDIZED REGRESSION COEFFICIENT appeared first on Analytics Vidhya.

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The quest for high-quality data

O'Reilly on Data

Moreover, the domain knowledge, which often is not encoded in the data (nor fully documented), is an integral part of this data (see this article from Forbes). In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. See this article on data integration status for details.

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Top 5 Statistical Techniques in Python

Sisense

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. Mastering statistical techniques and knowing how to implement them via a programming language are essential building blocks for advanced analytics. Linear regression.