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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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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 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

Neural networks

Artificial neural networks (ANN) are models inspired by the animal brain (highly evolved animals). A neural network is a network of neurons-units with inputs and outputs. For example, the input of a neuron can be a value related to the pixel of an image and the output of a neuron can be passed to another neuron and then another, and so on, thus creating a multilayered network. Neural networks contain adaptive elements, making them suitable to deal with nonlinear models and pattern recognition problems. We will again try to predict whether it is going to rain based on day-of-the-year and previous day values. Let's use the theanets Python library, which can be installed as follows:

$ pip3 install theanets nose_parameterized

One of the technical reviewers encountered an error, which was resolved by updating NumPy and SciPy. We first create an Experiment corresponding to a neural network and then train the network. Create a network with two input neurons and one output...

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