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Data Analysis with Python

Data Analysis with Python

By : David Taieb
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Data Analysis with Python

Data Analysis with Python

5 (1)
By: David Taieb

Overview of this book

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
Table of Contents (14 chapters)
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3
3. Accelerate your Data Analysis with Python Libraries
13
Index

Why choose Python?


Like many developers, when it came to building data-intensive projects, using Python wasn't my first choice. To be honest, having worked with Java for so many years, Scala seemed much more attractive to me at first, even though the learning curve was pretty steep. Scala is a very powerful language that elegantly combines object-oriented and functional programming, which is sorely lacking in Java (at least until Java 8 started to introduce lambda expressions).

Scala also provides a very concise syntax that translates into fewer lines of code, higher productivity, and ultimately fewer bugs. This comes in very handy, especially when a large part of your work is to manipulate data. Another reason for liking Scala is the better API coverage when using big data frameworks such as Apache Spark, which are themselves written in Scala. There are also plenty of other good reasons to prefer Scala, such as it's a strong typed system and its interoperability with Java, online documentation...

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Data Analysis with Python
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