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Beyond Guesswork: Leveraging Bayesian Statistics for Effective Article Title Selection

KDnuggets

The article discusses how Bayesian multi-armed bandit algorithms can optimize digital media title selection, surpassing traditional A/B testing methods, demonstrated with a Python example, to boost audience engagement and decision-making in content creation.

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The Impact of Generative AI on Media and Advertising

RandomTrees

The Impact of AI on Media 1. Shaping Digital Media Platforms Generative AI has revolutionized the sectors of digital media and has literally transformed into video editing, graphic design, and scriptwriting. Bias in Algorithms: AI models might perpetuate the biases existing in society.

Media 52
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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Even though such techniques can scale security solutions proportional to the service size, they bring their own set of challenges such as requiring labeled data samples, defining effective features, and finding appropriate algorithms.

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Consulting Case Study: Lookalike Models for Audience Expansion

WeCloudData

Precision vs Recall: i.e., “cost of targeting the wrong user is much smaller than the cost of failing to target the right user”. It showed our capability in handling large amount of data and provide the data-driven insights in new areas.

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Consulting Case Study: Lookalike Models for Audience Expansion

WeCloudData

Precision vs Recall: i.e., “cost of targeting the wrong user is much smaller than the cost of failing to target the right user”. It showed our capability in handling large amount of data and provide the data-driven insights in new areas.

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30+ Free Datasets for Your Data Science Projects in 2023

Knowledge Hut

Using algorithms and statistical models, Silver and other analysts make forecasts about politics, sports, the economy, and other topics. It is a leading provider of digital media and has released several high-profile scoops. Statistician Nate Silver founded FiveThirtyEight. The complete data dump can be found in the link below.

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Recommendation System Using Machine Learning | Examples & Types

U-Next

Example of Collaborative filtering algorithms: . The content-based filtering (CBF) algorithm makes suggestions based on specific item attributes by identifying similarities. The PVR algorithm was developed since it was so important for OTT (Over-the-Top) services to understand consumer preferences. The Code . Example: .