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Deep Learning Cookbook: Practical Recipes to Get Started Quickly 1st Edition

by Douwe Osinga (Author)
4.5 4.5 out of 5 stars 18 ratings
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Deep learning doesn�¢??t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you�¢??ll learn how to solve deep-learning problems for classifying and generating text, images, and music.

Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Author Douwe Osinga also provides a chapter with half a dozen techniques to help you if you�¢??re stuck. Examples are written in Python with code available on GitHub as a set of Python notebooks.

You�¢??ll learn how to:

  • Create applications that will serve real users
  • Use word embeddings to calculate text similarity
  • Build a movie recommender system based on Wikipedia links
  • Learn how AIs see the world by visualizing their internal state
  • Build a model to suggest emojis for pieces of text
  • Reuse pretrained networks to build an inverse image search service
  • Compare how GANs, autoencoders and LSTMs generate icons
  • Detect music styles and index song collections

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  1. ISBN-10
    149199584X
  2. ISBN-13
    978-1491995846
  3. Edition
    1st
  4. Publisher
    O'Reilly Media
  5. Publication date
    July 17, 2018
  6. Language
    English
  7. Dimensions
    7 x 0.5 x 9.1 inches
  8. Print length
    251 pages
  9. See all details
Next slide of product details

From the brand

Previous page
  2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniqu...
    AI Engineering: Building Applications with Foundation Models
    Deep Learning from Scratch: Building with Python from First Principles
    Hands-On Large Language Models: Language Understanding and Generation

    Machine Learning, AI & more

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  3. Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Build...
    Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications
    AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence
    Building Machine Learning Powered Applications: Going from Idea to Product

    Machine Learning

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  4. Hands-On Generative AI with Transformers and Diffusion Models
    AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning
    Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems
    AI-Assisted Programming: Better Planning, Coding, Testing, and Deployment

    Artificial Intelligence

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  5. Fundamentals of Deep Learning: Designing Next-Generation Machine Intelligence Algorithms
    Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play
    Deep Learning for Coders with fastai and PyTorch: AI Applications Without a PhD
    Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python

    Deep Learning

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  6. Practical Natural Language Processing: A Comprehensive Guide to Building Real-World NLP Systems
    Prompt Engineering for LLMs: The Art and Science of Building Large Language Model–Based Applications
    Designing Large Language Model Applications: A Holistic Approach to LLMs
    Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph

    Language Processing (NLP, LLM)

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  7. Sharing the knowledge of experts

    O'Reilly's mission is to change the world by sharing the knowledge of innovators. For over 40 years, we've inspired companies and individuals to do new things (and do them better) by providing the skills and understanding that are necessary for success.

    Our customers are hungry to build the innovations that propel the world forward. And we help them do just that.

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Editorial Reviews

About the Author

Douwe Osinga is an experienced Software Engineer, formerly with Google, and founder of three startups. He maintains a popular software project website, partly focused on machine learning (https://douweosinga.com/projects/machine_learning).

Product details

  • Publisher ‏ : ‎ O'Reilly Media; 1st edition (July 17, 2018)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 251 pages
  • ISBN-10 ‏ : ‎ 149199584X
  • ISBN-13 ‏ : ‎ 978-1491995846
  • Item Weight ‏ : ‎ 1 pounds
  • Dimensions ‏ : ‎ 7 x 0.5 x 9.1 inches
  • Customer Reviews:
    4.5 4.5 out of 5 stars 18 ratings

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4.5 out of 5 stars
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Top reviews from the United States

  • Douwe Osinga
    5.0 out of 5 stars This is a great book for anybody who has a decent background in ...
    Reviewed in the United States on August 1, 2018
    Verified Purchase
    This is a great book for anybody who has a decent background in writing software and an interest in getting started with Deep Learning. The book covers a wide variety of topics ranging from text classification and generation to image and music processing. The Python Notebooks accompanying the book make it easy to follow the code. The book is black and white which isn't ideal for some outputs. In these cases the Notebooks come in handy too.
    3 people found this helpful
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  • Violet Whitney
    5.0 out of 5 stars The best book for getting into deep learning!
    Reviewed in the United States on August 4, 2018
    Verified Purchase
    This book makes understanding deep learning a breeze. The simple diagrams and tone of the writing make it approachable and fun. The Python examples in the book are shared on GitHub to allow anyone to jump in with some Python knowledge.

    Highly highly recommend if you want to bring your deep learning from 0 to 60 fast!
    5 people found this helpful
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  • Serge Aurubin
    5.0 out of 5 stars Excellent book
    Reviewed in the United States on October 18, 2018
    Verified Purchase
    Excellent resource and fast shipping
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  • Antonio Gulli
    5.0 out of 5 stars Top 3 book for practical approach to deep learning,
    Reviewed in the United States on November 22, 2018
    There are two classes of books for deep learning: the theoretical ones and the practical ones. If you are starting, then my suggestion is to pick a book for each class and iterate back and forward between classes.
    Now, this book is in my top 3 books for the 'practical ones' class. Very well, written with large coverage of the most modern aspects of Deep learning. I particularly enjoyed the chapter on music analysis - which is normally not covered by other books - and all the comprehensive discussions about embeddings. Only Deep Reinforcement Learning is not covered by the book and that's the reason why I do not position the book in the top 2. Overall it's a book I definitively recommend. The github repository is also well done.
    11 people found this helpful
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  • chaizzilla
    5.0 out of 5 stars Douwe the guy who made all those cool things with data waaaaaaaay back when!
    Reviewed in the United States on August 7, 2019
    I was a huuuuuge fan of yours and you inspired me to think way more playfully and experimentally about the stuff I already liked doing and was heading into a GIS cert study to augment & try and keep my career away from abstract stuff.... but I ended up in finance for nerly a decade anyway; I just put this on my wish list because all my books are stuck on the other side of the country and I've had my resistance to buying electronic copies instead of a book I can see without a second monitor, etc... -- totally schooled. I can only imagine the uniquely creative wit and utility and perfection you put into this book.... absolutely stoked to see it. Congrats on doing stuff we both love! DATA <3
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  • David M
    5.0 out of 5 stars Well Written
    Reviewed in the United States on August 5, 2018
    Very useful book, beautifully written and well explained.
    2 people found this helpful
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Top reviews from other countries

  • Peter Jackson
    4.0 out of 5 stars Well written.
    Reviewed in Canada on November 23, 2018
    Verified Purchase
    Well written, but some of the sample code needs to be modified before it would run.
    Report