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    Data Analysis with Python (ebook)(audiobook)(audiobook) Książka w języku angielskim

    Okładka książki/ebooka Data Analysis with Python

    Okładka książki Data Analysis with Python

    Okładka książki Data Analysis with Python

    Okładka książki Data Analysis with Python

    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    491
    3w1 w pakiecie:
    PDF
    ePub
    Mobi

    Ebook

    129,00 zł

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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

    • Bridge your data analysis with the power of programming, complex algorithms, and AI
    • Use Python and its extensive libraries to power your way to deeper data insight
    • 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
    • Work with AI algorithms, TensorFlow, graphs, natural language processing, and time series
    • 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 established developers who want to bridge the gap between programmers and data scientists. With the introduction of PixieDust from its creator, the book will also be a great desk companion for the already accomplished Data Scientist. Some fluency in data interpretation and visualization is also assumed since this book addresses data professionals such as business and general data analysts. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.

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