Wed.Aug 31, 2022

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The Difference Between Training and Testing Data in Machine Learning

KDnuggets

When building a predictive model, the quality of the results depends on the data you use. In order to do so, you need to understand the difference between training and testing data in machine learning.

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Getting Started with the KRaft Protocol

Confluent

Kafka Raft lets you use Apache Kafka without ZooKeeper by consolidating metadata management. Here’s how you can learn and do more with KRaft.

Kafka 76
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Machine Learning Metadata Store

KDnuggets

In this article, we will learn about metadata stores, the need for them, their components, and metadata store management.

Metadata 156
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Machine Learning in the Enterprise: Use Cases & Challenges

KDnuggets

This article provides insights into how leading data scientists are embracing machine learning in their organizations and covers some of the major ML challenges and trends in the enterprise.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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KDnuggets News, August 31: The Complete Data Science Study Roadmap • 7 Techniques to Handle Imbalanced Data

KDnuggets

The Complete Data Science Study Roadmap • 7 Techniques to Handle Imbalanced Data • 3 Ways to Append Rows to Pandas DataFrames • The Bias-Variance Trade-off • How to Package and Distribute Machine Learning Models with MLFlow.