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Pluralsight

Launching into Machine Learning

via Pluralsight

Overview

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way so as to support experimentation.

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way so as to support experimentation.

Topics:
  • Introduction to Course
  • Improve Data Quality and Exploratory Data Analysis
  • Practical ML
  • Optimization
  • Generalization and Sampling
  • Summary
  • Course Resources

Taught by

Google Cloud

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