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Artificial Intelligence with Python

Artificial Intelligence with Python

By : Prateek Joshi
3.6 (34)
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Artificial Intelligence with Python

Artificial Intelligence with Python

3.6 (34)
By: Prateek Joshi

Overview of this book

Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more. Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents (17 chapters)
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Chapter 2. Classification and Regression Using Supervised Learning

In this chapter, we are going to learn about classification and regression of data using supervised learning techniques. By the end of this chapter, you will know about these topics:

  • What is the difference between supervised and unsupervised learning?
  • What is classification?
  • How to preprocess data using various methods
  • What is label encoding?
  • How to build a logistic regression classifier
  • What is Naïve Bayes classifier?
  • What is a confusion matrix?
  • What are Support Vector Machines and how to build a classifier based on that?
  • What is linear and polynomial regression?
  • How to build a linear regressor for single variable and multivariable data
  • How to estimate housing prices using Support Vector Regressor
CONTINUE READING
83
Tech Concepts
36
Programming languages
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Artificial Intelligence with Python
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