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Python Machine Learning (Wiley)

You're reading from   Python Machine Learning (Wiley) Python makes machine learning easy for beginners and experienced developers

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Product type Paperback
Published in Apr 2019
Publisher Wiley
ISBN-13 9781119545637
Length 320 pages
Edition 1st Edition
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Author (1):
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Wei-Meng Lee Wei-Meng Lee
Author Profile Icon Wei-Meng Lee
Wei-Meng Lee
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Table of Contents (16) Chapters Close

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

What Is Machine Learning?

If you have ever written a program, you will be familiar with the diagram shown in Figure 1.1. You write a program, feed some data into it, and get your output. For example, you might write a program to perform some accounting tasks for your business. In this case, the data collected would include your sales records, your inventory lists, and so on. The program would then take in the data and calculate your profits or loss based on your sales records. You may also perhaps churn out some nice and fanciful charts showing your sales performance. In this case, the output is the profit/loss statement, as well as other charts.

Diagram of a traditional programming, in which the data and the program produce the output.

Figure 1.1: In traditional programming, the data and the program produce the output

For many years, traditional desktop and web programming have dominated the landscape, and many algorithms and methodologies have evolved to make programs run more efficiently. In more recent years, however, machine learning has taken over the programming world...

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