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Comet for Data Science

You're reading from   Comet for Data Science Enhance your ability to manage and optimize the life cycle of your data science project

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781801814430
Length 402 pages
Edition 1st Edition
Tools
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Author (1):
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Angelica Lo Duca Angelica Lo Duca
Author Profile Icon Angelica Lo Duca
Angelica Lo Duca
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1 – Getting Started with Comet
2. Chapter 1: An Overview of Comet FREE CHAPTER 3. Chapter 2: Exploratory Data Analysis in Comet 4. Chapter 3: Model Evaluation in Comet 5. Section 2 – A Deep Dive into Comet
6. Chapter 4: Workspaces, Projects, Experiments, and Models 7. Chapter 5: Building a Narrative in Comet 8. Chapter 6: Integrating Comet into DevOps 9. Chapter 7: Extending the GitLab DevOps Platform with Comet 10. Section 3 – Examples and Use Cases
11. Chapter 8: Comet for Machine Learning 12. Chapter 9: Comet for Natural Language Processing 13. Chapter 10: Comet for Deep Learning 14. Chapter 11: Comet for Time Series Analysis 15. Other Books You May Enjoy

Reviewing the main machine learning models

A machine learning model is an algorithm that can make predictions for some unseen data based on what it has learned from some training data. As already discussed in the preceding section, you can distinguish machine learning models into two categories, which depend on the specific task you want to solve: supervised models and unsupervised models.

Many machine learning models exist in the literature. In this section, you will review the most popular models used to perform supervised learning and unsupervised learning. We will focus on the following models in detail:

  • Supervised learning
  • Unsupervised learning

In the remainder of the section, you will review an introduction to the most popular machine learning models. For more details, you can read the books proposed in the Further reading section. Let’s start with the first category of models: supervised learning.

Supervised learning

A supervised algorithm...

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