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Data Analysis with Python (eBook)

A Modern Approach
eBook Download: EPUB
2018
490 Seiten
Packt Publishing (Verlag)
978-1-78995-819-5 (ISBN)

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Data Analysis with Python -  Taieb David Taieb
35,41 € (CHF 34,60)
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36,59 € (CHF 35,75)
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Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.




Key Features



  • Bridge your data analysis with the power of programming, complex algorithms, and AI


  • Use Python and its extensive libraries to power your way to new levels of data insight


  • Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series


  • Explore this modern approach across with key industry case studies and hands-on projects





Book Description



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.




What you will learn



  • A new toolset that has been carefully crafted to meet for your data analysis challenges


  • Full and detailed case studies of the toolset across several of today's key industry contexts


  • Become super productive with a new toolset across Python and Jupyter Notebook


  • Look into the future of data science and which directions to develop your skills next



Who this book is for



This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.


Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.Key FeaturesBridge your data analysis with the power of programming, complex algorithms, and AIUse Python and its extensive libraries to power your way to new levels of data insightWork with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time seriesExplore this modern approach across with key industry case studies and hands-on projectsBook DescriptionData 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.What you will learnA new toolset that has been carefully crafted to meet for your data analysis challengesFull and detailed case studies of the toolset across several of today's key industry contextsBecome super productive with a new toolset across Python and Jupyter NotebookLook into the future of data science and which directions to develop your skills nextWho this book is forThis book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.
Erscheint lt. Verlag 31.12.2018
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Programmiersprachen / -werkzeuge
Schlagworte AI • algorithms • Artificial Intelligence • Data Analysis • Data Science • Jupyter • machine learning • Python • tensorflow
ISBN-10 1-78995-819-9 / 1789958199
ISBN-13 978-1-78995-819-5 / 9781789958195
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Dateiformat: EPUB (Electronic Publication)
EPUB ist ein offener Standard für eBooks und eignet sich besonders zur Darstellung von Belle­tristik und Sach­büchern. Der Fließ­text wird dynamisch an die Display- und Schrift­größe ange­passt. Auch für mobile Lese­geräte ist EPUB daher gut geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür die kostenlose Software Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür eine kostenlose App.
Geräteliste und zusätzliche Hinweise

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

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