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In an effort to reach non-technical readers, Dataiku has released a new report that offers a guide to machine learning basics. And no, you don’t have to be an AI expert to understand the content—complete with easy-to-understand diagrams and illustrations.
The report, “Machine Learning Basics: An Illustrated Guide for Non-Technical Readers,” starts out by exploring definitions of basic machine learning terms, including the topic itself. What is machine learning? Dataiku says it can be boiled down to one word: Algorithms.
To fully understand machine learning, one must have a basic understanding of data science concepts, as well. Next up, the report offers definitions of 10 fundamental terms for data science and machine learning. Think model, regression, classification and more.
Many businesses today use machine learning through tools such as prediction algorithms, of which the guide explores the most popular: linear models, tree-based models and neural networks...
The full report from Dataiku covered the following topics:
- Machine Learning Concepts for Everyone
- An Introduction to Key Data Science Concepts
- Top Prediction Algorithms
- How to Evaluate Models
- Introducing the K-Fold Strategy and the Hold-Out Strategy
- K-Means Clustering Algorithms in Action
- For Further Exploration
- About Dataiku
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| Photo: insideBIGDATA |
10 Tips for Building Effective Machine Learning Models
"In this contributed article, Wayne Thompson, Chief Data Scientist at SAS, provides 10 tips for organizations who want to use machine learning more effectively."
Source: insideBIGDATA
