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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources

Chapter 10. Predictive Analytics and Machine Learning

Predictive analytics and machine learning have recently been accepted into mainstream data science and data analytics by many industries. They are now compared to other fields, and, without a doubt, we can expect a lot of rapid growth. It is even predicted that machine learning will accelerate so fast that within mere decades human labor will be replaced by intelligent machines (see http://en.wikipedia.org/wiki/Technological_singularity). The current state of art for artificial general intelligence (AGI) is far from that utopia, but machine learning has come a long way, and is being used in self-driving cars, chatbots, and AI-based assistants, such as Amazon's Alexa, Apple's Siri, and Ok Google. A lot of computing power and data is still needed to make even simple decisions, such as determining whether pictures on the Internet contain dogs or cats. Predictive analytics uses a variety of techniques, including machine...

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