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    Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson - okladka książki

    Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson - okladka książki

    Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson - audiobook MP3

    Python: End-to-end Data Analysis. Leverage the power of Python to clean, scrape, analyze, and visualize your data Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson - audiobook CD

    Autorzy:
    Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Dostępne formaty:
         PDF
         ePub
         Mobi
    Data analysis is the process of applying logical and analytical reasoning to study each component of data present in the system. Python is a multi-domain, high-level, programming language that offers a range of tools and libraries suitable for all purposes, it has slowly evolved as one of the primary languages for data science. Have you ever imagined becoming an expert at effectively approaching data analysis problems, solving them, and extracting all of the available information from your data? If yes, look no further, this is the course you need!
    In this course, we will get you started with Python data analysis by introducing the basics of data analysis and supported Python libraries such as matplotlib, NumPy, and pandas. Create visualizations by choosing color maps, different shapes, sizes, and palettes then delve into statistical data analysis using distribution algorithms and correlations. You’ll then find your way around different data and numerical problems, get to grips with Spark and HDFS, and set up migration scripts for web mining. You’ll be able to quickly and accurately perform hands-on sorting, reduction, and subsequent analysis, and fully appreciate how data analysis methods can support business decision-making. Finally, you will delve into advanced techniques such as performing regression, quantifying cause and effect using Bayesian methods, and discovering how to use Python’s tools for supervised machine learning.
    The course provides you with highly practical content explaining data analysis with Python, from the following Packt books:
    1. Getting Started with Python Data Analysis.
    2. Python Data Analysis Cookbook.
    3. Mastering Python Data Analysis.
    By the end of this course, you will have all the knowledge you need to analyze your data with varying complexity levels, and turn it into actionable insights.

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    O autorach książki

    Ivan Idris jest programistą, twórcą hurtowni danych i analitykiem biznesu. Słynie ze schludnego kodu i z interesującego sposobu pisania.

    Luiz Felipe Martins holds a PhD in applied mathematics from Brown University and has worked as a researcher and educator for more than 20 years. His research is mainly in the field of applied probability. He has been involved in developing code for the open source homework system, WeBWorK, where he wrote a library for the visualization of systems of differential equations. He was supported by an NSF grant for this project. Currently, he is an Associate Professor in the Department of Mathematics at Cleveland State University, Cleveland, Ohio, where he has developed several courses in applied mathematics and scientific computing. His current duties include coordinating all first-year calculus sessions.
    Martin Czygan studied German literature and computer science in Leipzig, Germany. He has been working as a software engineer for more than 10 years. For the past eight years, he has been diving into Python, and is still enjoying it. In recent years, he has been helping clients to build data processing pipelines and search and analytics systems.
    Phuong Vo.T.H has a MSc degree in computer science, which is related to machine learning. After graduation, she continued to work in some companies as a data scientist. She has experience in analyzing users' behavior and building recommendation systems based on users' web histories. She loves to read machine learning and mathematics algorithm books, as well as data analysis articles.
    Magnus Vilhelm Persson is a scientist with a passion for Python and open source software usage and development. He obtained his PhD in Physics/Astronomy from Copenhagen Universitys Centre for Star and Planet Formation (StarPlan) in 2013. Since then, he has continued his research in Astronomy at various academic institutes across Europe. In his research, he uses various types of data and analysis to gain insights into how stars are formed. He has participated in radio shows about Astronomy and also organized workshops and intensive courses about the use of Python for data analysis. You can check out his web page at https://vilhelm.nu.

    Ivan Idris, Luiz Felipe Martins, Martin Czygan, Phuong Vo.T.H, Magnus Vilhelm Persson - pozostałe książki

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