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    Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models Ali Madani, Stephen MacKinnon

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models Ali Madani, Stephen MacKinnon - okladka książki

    Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models Ali Madani, Stephen MacKinnon - okladka książki

    Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models Ali Madani, Stephen MacKinnon - audiobook MP3

    Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models Ali Madani, Stephen MacKinnon - audiobook CD

    Autorzy:
    Ali Madani, Stephen MacKinnon
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    344
    Dostępne formaty:
         PDF
         ePub
    Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies.
    By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.

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    O autorze książki

    Ali Madani worked as the director of machine learning at Cyclica Inc leading AI technology development front of Cyclica for drug discovery before acquisition of Cyclica by Recursion Pharmaceuticals. Ali completed his PhD at University of Toronto focusing on machine learning modeling in cancer setting and attained a Master of Mathematics from the University of Waterloo. As a believer in industry-oriented education and pro-democratization of knowledge, Ali has actively educated students and professionals through international workshops and courses on basic and advanced high-quality machine learning modeling. When not immersed in machine learning modeling and teaching, Ali enjoys exercising, cooking and traveling with his partner.

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