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Data Analysis with Python

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

Product type Paperback

Published in Dec 2018

Publisher Packt

ISBN-13 9781789950069

Length 490 pages

Edition 1st Edition

Languages

Python

Tools

Jupyter

Concepts

Data Analysis

Author (1):

David Taieb

View More author details

Table of Contents (14) Chapters

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

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Index

Index

A

access tokens
- reference link / Display – a simple interactive API for data visualization
adjacency list / Graph representations
adjacency matrix / Graph representations
AlphaZero
- reference link / Forward thinking – what to expect for AI and data science
Anaconda
- reference link / Introducing PixieDust
Apache Hadoop
- URL / Getting started with Apache Spark
Apache Kafka
- reference link / Back to our sentiment analysis of Twitter hashtags project
Apache Spark
- reference link / Back to our sentiment analysis of Twitter hashtags project
- about / Getting started with Apache Spark
- URL / Getting started with Apache Spark
- architecture / Apache Spark architecture
- notebooks, configuring / Configuring Notebooks to work with Spark
Apache Spark, components
- Spark SQL / Apache Spark architecture
- Spark Streaming / Apache Spark architecture
- MLlib / Apache Spark architecture
- GraphX / Apache Spark architecture...

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Authors (1)

David Taieb

David Taieb

David Taieb is the Distinguished Engineer for the Watson and Cloud Platform Developer Advocacy team at IBM, leading a team of avid technologists on a mission to educate developers on the art of the possible with data science, AI and cloud technologies. He's passionate about building open source tools, such as the PixieDust Python Library for Jupyter Notebooks, which help improve developer productivity and democratize data science. David enjoys sharing his experience by speaking at conferences and meetups, where he likes to meet as many people as possible.

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