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Data Analysis with Python

You're reading from   Data Analysis with Python A Modern Approach

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950069
Length 490 pages
Edition 1st Edition
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Author (1):
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David Taieb David Taieb
Author Profile Icon David Taieb
David Taieb
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Table of Contents (14) Chapters Close

Preface 1. Programming and Data Science – A New Toolset FREE CHAPTER 2. Python and Jupyter Notebooks to Power your Data Analysis 3. Accelerate your Data Analysis with Python Libraries 4. Publish your Data Analysis to the Web - the PixieApp Tool 5. Python and PixieDust Best Practices and Advanced Concepts 6. Analytics Study: AI and Image Recognition with TensorFlow 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis 10. The Future of Data Analysis and Where to Develop your Skills A. PixieApp Quick-Reference Other Books You May Enjoy Index

Chapter 10. The Future of Data Analysis and Where to Develop your Skills

"We are creating and hiring to fill "new collar" jobs – entirely new roles in areas such as cybersecurity, data science, artificial intelligence and cognitive business."

Ginni Rometty, IBM Chairman, and CEO

Once again, let me thank you and congratulate you, the reader, for the long journey of reading through these long chapters and perhaps trying some or all of the sample code provided. I tried to provide a good mix between diving into the fundamentals of a particular topic, such as deep learning or time series analysis, and giving comprehensive example code for the practitioner. I especially hope that you found the idea of tightly integrating the data science analytics with the PixieApp application programming model in a single Jupyter Notebook interesting and novel. But, most importantly, I hope...

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