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The DataHour: Introduction to MLOps

Analytics Vidhya

Anish has been a Lead Data Science consultant for various Fortune 500 customers for a long time and has helped over 2000 employees into the Data Science profession. Introduction Anish Mahapatra has is conducting an interactive DataHour session with us.

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Building a Content-Based Recommendation System

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Back in 2000, people used to purchase groceries from their local hypermarts. However, in the last 20 years, several online e-commerce stores have been launched.

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Top 9 Considerations for Enterprise AI

Rocket-Powered Data Science

The Web/e-Commerce tidal wave also brought a lot of hype and FOMO, which ultimately led to the Internet bubble burst (the dot-com crash) in the early 2000’s. That had and continues to have a very big and long-lasting impact. Are we heading for another round of hype / high hopes / exhilaration / FOMO / crash and burn with AI?

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IBM and Data Science are Helping Save the World through Call for Code

Business Over Broadway

million people have been directly affected by natural disasters since 2000. Even though natural events such as floods, earthquakes or hurricanes are inevitable, I believe that their impact can be mitigated through the application of data and analytics. Data is the Fuel; Data Science is the Engine. Help from IBM.

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Discovering the Wonders of Data-Driven PPC Marketing

Smart Data Collective

Big data can be useful for all of these aspects of your campaign. PPC Hero talked about the evolving role of data science in PPC. By carefully structuring your campaigns with big data, you can benefit from profitable PPC campaigns that deliver long-standing results for your business.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Other techniques include simple re-sampling, where the minority class is continuously re-sampled until the number of obtained observations matches the size of the majority class, and focused under-sampling, where the discarded observations from the majority class are carefully selected to be away from the decision boundary (Japkowicz, 2000).

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How to Use Apache Iceberg in CDP’s Open Lakehouse

Cloudera

Exploratory data science and visualization: Access Iceberg tables through auto-discovered CDW connection in CML projects. Our imported flights table now contains the same data as the existing external hive table and we can quickly check the row counts by year to confirm: year _c1. 9 2000 5683047. …. 1 2008 7009728.