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AutoML

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May 1, 2024 Updated May 11, 2025 25 minute read
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Automated Machine Learning, or AutoML, represents a significant shift in the field of Artificial Intelligence and Machine Learning. At its core, AutoML aims to automate the time-consuming, iterative tasks of machine learning model development. This allows data scientists, analysts, and even developers with limited machine learning expertise to build and deploy models with greater efficiency and scale. Imagine being able to automatically select the best algorithm for your data, fine-tune its parameters, and prepare your data for analysis, all with minimal manual intervention. This is the promise of AutoML.

Path to AutoML

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We've curated 24 courses to help you on your path to AutoML. Use these to develop your skills, build background knowledge, and put what you learn to practice.
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Reading list

We've selected one books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in AutoML.
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Machine Learning for Data Streams
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Explores the use of AutoML in startups. It provides a comprehensive overview of the field and valuable resource for researchers and practitioners alike.
Machine Learning for Data Streams: with Practical...
Hardcover
$$$
Machine Learning for Data Streams: with Practical...
Kindle Edition
$$
Relevant careers
Machine Learning Engineer
Data Scientist
Cloud Architect
DevOps Engineer
Data Analyst
Software Engineer
Product Manager
Business Analyst
Project Manager
Data Warehouse Engineer
Related topics
Machine Learning
Artificial Intelligence
Deep Learning
Data Science
Cloud Computing
Natural Language Processing
Image Processing
Computer Vision
Time Series Analysis
Predictive Analytics
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