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Getting Started with Python for the Internet of Things

You're reading from   Getting Started with Python for the Internet of Things Leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi

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Product type Course
Published in Feb 2019
Publisher
ISBN-13 9781838555795
Length 732 pages
Edition 1st Edition
Languages
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Authors (5):
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Tim Cox Tim Cox
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Tim Cox
Prof. Diwakar Vaish Prof. Diwakar Vaish
Author Profile Icon Prof. Diwakar Vaish
Prof. Diwakar Vaish
Sai Yamanoor Sai Yamanoor
Author Profile Icon Sai Yamanoor
Sai Yamanoor
Steven Lawrence Fernandes Steven Lawrence Fernandes
Author Profile Icon Steven Lawrence Fernandes
Steven Lawrence Fernandes
Srihari Yamanoor Srihari Yamanoor
Author Profile Icon Srihari Yamanoor
Srihari Yamanoor
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Table of Contents (37) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Getting Started with a Raspberry Pi 3 Computer FREE CHAPTER 2. Dividing Text Data and Building Text Classifiers 3. Using Python for Automation and Productivity 4. Predicting Sentiments in Words 5. Detecting Edges and Contours in Images 6. Building Face Detector and Face Recognition Applications 7. Using Python to Drive Hardware 8. Sensing and Displaying Real-World Data 9. Building Neural Network Modules for Optical Character Recognition 10. Arithmetic Operations, Loops, and Blinky Lights 11. Conditional Statements, Functions, and Lists 12. Communication Interfaces 13. Data Types and Object-Oriented Programming in Python 14. File I/O and Python Utilities 15. Requests and Web Frameworks 16. Awesome Things You Could Develop Using Python 17. Robotics 101 18. Using GPIOs as Input 19. Making a Gardener Robot 20. Basics of Motors 21. Bluetooth-Controlled Robotic Car 22. Sensor Interface for Obstacle Avoidance 23. Making Your Own Area Scanner 24. Basic Switching 25. Recognizing Humans with Jarvis 26. Making Jarvis IoT Enabled 27. Giving Voice to Jarvis 28. Gesture Recognition 29. Machine Learning 30. Making a Robotic Arm 1. Other Books You May Enjoy Index

Chapter 29. Machine Learning

Robots and computers from its primitive days to even right now are being programmed to do a set of activities. These activities can be very large. Hence, to develop complex programs, there is a need for a lot of software engineers who work day and night to achieve a certain functionality. This is workable when the problem is well defined. But what about situations when the problem is also way complex?

Learning is something that has made us humans what we are. Our experiences molded us to adapt to situations in a better and a more efficient way. Every time we do something, we know more. This makes us better at doing that task over a period of time. It is said practice makes a man perfect, and it is learning through doing things again and again that makes us better.

However, let us step back and define what learning is? I would like to quote Google here according to it, It is a knowledge acquired through study, experience or being taught. So, learning is basically...

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