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Python Machine Learning (Wiley)
Python Machine Learning (Wiley)

Python Machine Learning (Wiley): Python makes machine learning easy for beginners and experienced developers

By Wei-Meng Lee
AU$19.99 per month
Book Apr 2019 320 pages 1st Edition
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Key benefits

  • Get a detailed introduction to machine learning
  • Study various supervised and unsupervised algorithms
  • Discover the problem-solving abilities of Python through real-life scenarios

Description

With computing power increasing exponentially and costs decreasing at the same time, this is the best time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. Python Machine Learning begins by covering some fundamental libraries used in Python that make machine learning possible. You'll learn how to manipulate arrays of numbers with NumPy and use pandas to deal with tabular data. Once you have a firm foundation in the basics, you'll explore machine learning using Python and the scikit-learn libraries. You'll learn how to visualize data by plotting different types of charts and graphs using the matplotlib library. You'll gain a solid understanding of how the various machine learning algorithms work behind the scenes. The later chapters explore the common machine learning algorithms, such as regression, clustering, and classification, and discuss how to deploy the models that you have built, so that they can be used by client applications running on mobile and desktop devices. By the end of the book, you'll have all the knowledge you need to begin machine learning using Python.

What you will learn

Perform machine learning using the Microsoft Azure Machine Learning Studio Deploy the models to be used by other applications Manipulate tabular data using pandas Create data visualizations using Matplotlib Form clusters of unlabelled data using the K-means algorithms Use scikit-learn to perform linear regression on a dataset

Product Details

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Publication date : Apr 4, 2019
Length 320 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781119545637
Category :

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Product Details


Publication date : Apr 4, 2019
Length 320 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781119545637
Category :

Table of Contents

16 Chapters
1. Cover Chevron down icon Chevron up icon
2. Introduction Chevron down icon Chevron up icon
3. CHAPTER 1: Introduction to Machine Learning Chevron down icon Chevron up icon
4. CHAPTER 2: Extending Python Using NumPy Chevron down icon Chevron up icon
5. CHAPTER 3: Manipulating Tabular Data Using Pandas Chevron down icon Chevron up icon
6. CHAPTER 4: Data Visualization Using matplotlib Chevron down icon Chevron up icon
7. CHAPTER 5: Getting Started with Scikit‐learn for Machine Learning Chevron down icon Chevron up icon
8. CHAPTER 6: Supervised Learning—Linear Regression Chevron down icon Chevron up icon
9. CHAPTER 7: Supervised Learning—Classification Using Logistic Regression Chevron down icon Chevron up icon
10. CHAPTER 8: Supervised Learning—Classification Using Support Vector Machines Chevron down icon Chevron up icon
11. CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN) Chevron down icon Chevron up icon
12. CHAPTER 10: Unsupervised Learning—Clustering Using K‐Means Chevron down icon Chevron up icon
13. CHAPTER 11: Using Azure Machine Learning Studio Chevron down icon Chevron up icon
14. CHAPTER 12: Deploying Machine Learning Models Chevron down icon Chevron up icon
15. Index Chevron down icon Chevron up icon
16. End User License Agreement Chevron down icon Chevron up icon

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