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

Analytics Vidhya

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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Campus Recruitment: A Classification Problem with Logistic Regression

Analytics Vidhya

And our goal is to create a predictive model, such as Logistic Regression, etc. so that when we give the characteristics of a candidate, the model can predict whether they will recruit. Introduction In this project, we will be focusing on data from India.

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How Data Cleansing Helps Predictive Modeling Efforts

TDAN

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time. In a world where big data is becoming more popular and the use of predictive modeling is on the rise, there are steps […].

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Proposals for model vulnerability and security

O'Reilly on Data

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models. 4) AIOps increasingly became a focus in AI strategy conversations. And the goodness doesn’t stop there.

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DaVita’s technology strategy driven by the ‘power of purpose’

CIO Business Intelligence

Our digital transformation strategy is centered around establishing a consumer-oriented model that helps us customize chronic care management based on the ever-changing conditions of each patient.” Tim Scannell: How much of a role do technologies like data analytics and AI play in DaVita’s overall technology and business strategy?

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How to Set AI Goals

O'Reilly on Data

As AI maturity increases, a non-incremental, holistic, and organization-wide AI vision and strategy should be created to achieve hierarchically-aligned AI goals of varying granularity—goals that drive all AI initiatives and development. In an early stage of AI maturity, we can build AI solutions that reduce search friction (e.g.,