Practical Deep Learning: A Python-Based Introduction, (Paperback)
Practical Deep Learning teaches total beginners how to build datasets and train neural networks for DL projects. This is the book you've been waiting for if you've been curious about machine learning.
Practical Deep Learning: A Python-Based Introduction, (Paperback)
Artikelnr.: 64176255

Practical Deep Learning: A Python-Based Introduction, (Paperback)

Artikelnr.: 64176255

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Practical Deep Learning teaches total beginners how to build datasets and train neural networks for DL projects. This is the book you've been waiting for if you've been curious about machine learning.
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Wat opvalt

Hands-On Approach
Offers a practical, hands-on learning experience, enabling readers to apply deep learning concepts using Python, making it ideal for beginners seeking applicable skills.
Comprehensive Coverage
Covers a wide array of topics in deep learning, from basics to advanced techniques, ensuring that readers gain a thorough understanding of the field.
Accessible Format
Written in an easy-to-understand language, this book is designed for learners at all levels, making complex concepts more accessible to a broader audience.

Productdetails

Shop Practical Deep Learning: A Python-Based Introduction, (Paperback) online at a best price in Belgium. 670313944
  • Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you've been curious about artificial intelligence and machine learning but didn't know where to start, this is the book you've been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math--the book will cover the rest. After an introduction to Python, you'll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models' performance. You'll also learn: How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector MachinesHow neural networks work and how they're trainedHow to use convolutional neural networksHow to develop a successful deep learning model from scratch You'll conduct experiments along the way, building to a final case study that incorporates everything you've learned. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateFebruary, 2021
Pages464
Reading levelGeneral
SubgenreData Science
Series titleNo Series
Edition1
PublisherNo Starch Press
Original languagesEnglish
LanguageEnglish
Edu focusTechnology
Educational levelHigh School
Is collectibleN
IllustratorKevin Howdeshell
Binding typePerfect Binding
Recording time0 min
Retail packagingSingle Piece
Assembled product dimensions (l x w x h)7.00 x 1.30 x 9.20 in (17.8 x 3.3 x 23.4 cm)
Assembled product weight1.94 lb (880 grams)
Bisac subject headingComputers

Voor wie is dit geschikt?

Suitable For
  • Beginners in AI

    Perfect for those new to artificial intelligence and deep learning concepts, providing clear explanations and practical examples.

  • Python Programmers

    Ideal for existing Python developers wanting to enhance their skills in deep learning applications using familiar programming language.

  • Data Scientists

    Beneficial for data scientists looking to incorporate deep learning techniques into their data analysis and machine learning workflows.

Not Suitable For
  • Advanced Users

    Not ideal for experienced deep learning practitioners seeking advanced theories or cutting-edge techniques beyond basic frameworks.

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  • vraag: What prerequisites are needed for this book?

    antwoord: Basic familiarity with computer programming and high school math.
  • vraag: What will I learn from this book?

    antwoord: How to build training datasets, work with machine learning models, understand neural networks, and develop deep learning models from scratch.
  • vraag: Does the book focus on theory or practical application?

    antwoord: The book focuses on practical applications by teaching how to build and train models for deep learning projects.

Ronald T Kneusel All Books Editorial Review

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