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    Python: Real-World Data Science. Real-World Data Science Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Python: Real-World Data Science. Real-World Data Science Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka - okladka książki

    Python: Real-World Data Science. Real-World Data Science Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka - okladka książki

    Python: Real-World Data Science. Real-World Data Science Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka - audiobook MP3

    Python: Real-World Data Science. Real-World Data Science Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka - audiobook CD

    Autorzy:
    Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Dostępne formaty:
         PDF
         ePub
         Mobi
    The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you’ll have gained key skills and be ready for the material in the next module.
    The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it’s time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls.

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    O autorach książki

    Fabrizio Romano was born in Italy in 1975. He holds a master's degree in Computer Science Engineering from the University of Padova. He’s been working as a professional software developer since 1999. Fabrizio has been part of Sohonet’s Product Team since 2016. In 2020, the Television Academy honored them with an Emmy Award in Engineering Development for advancing remote collaboration.

    Dusty Phillips jest kanadyjskim programistą i autorem książek o programowaniu. Pracował dla rządów, startupów i sieci społecznościowych. Obecnie zajmuje się pisaniem powieści fantastycznych.

    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.
    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.
    Robert Layton is a data scientist investigating data-driven applications to businesses across a number of sectors. He received a PhD investigating cybercrime analytics from the Internet Commerce Security Laboratory at Federation University Australia, before moving into industry, starting his own data analytics company dataPipeline. Next, he created Eureaktive, which works with tech-based startups on developing their proof-of-concepts and early-stage prototypes. Robert also runs the LearningTensorFlow website, which is one of the world's premier tutorial websites for Google's TensorFlow library.

    Robert is an active member of the Python community, having used Python for more than 8 years. He has presented at PyConAU for the last four years and works with Python Charmers to provide Python-based training for businesses and professionals from a wide range of organisations.

    Robert can be best reached via Twitter @robertlayton

    Sebastian Raschka jest ekspertem w dziedzinie analizy danych i uczenia maszynowego. Obecnie przygotowuje doktorat na Michigan State University z metod obliczeniowych w biologii statystycznej. Biegle posługuje się Pythonem. Raschka bierze również udział w różnych projektach open source i wdraża nowe metody uczenia maszynowego. W wolnym czasie pracuje nad modelami predykcyjnymi dyscyplin sportowych. Jeżeli nie siedzi przed monitorem, chętnie uprawia sport.

    Fabrizio Romano, Dusty Phillips, Phuong Vo.T.H, Martin Czygan, Robert Layton, Sebastian Raschka - pozostałe książki

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