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    1. Data och IT
    2. Informationsteknik: allmänt

    Data Analysis with Python

    A Modern Approach

    AvDavid Taieb

    Häftad, Engelska, 2018

    584 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.

    Produktinformation

    • Utgivningsdatum:2018-12-31
    • Mått:191 x 235 x 26 mm
    • Vikt:906 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:490
    • Förlag:Packt Publishing Limited
    • ISBN:9781789950069

    Utforska kategorier

    • Informationsteknik: allmänt inom Data och IT

    Mer om författaren

    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.

    Innehållsförteckning

    • Table of ContentsProgramming and Data Science Python and Jupyter Notebooks to Power your Data AnalysisAccelerate your Data Analysis with Python LibrariesPublish your Data Analysis to the Web - the PixieApp ToolPython and PixieDust Best Practices and Advanced ConceptsAnalytics Study: AI and Image Recognition with TensorFlowAnalytics Study: NLP and Big Data with Twitter Sentiment AnalysisAnalytics Study: Prediction - Financial Time Series Analysis and ForecastingAnalytics Study: Graph Algorithms - US Domestic Flight Data AnalysisThe Future of Data Analysis and Where to Develop your Skills