BookShared
  • MEMBER AREA    
  • Deep Learning with Python

    (By François Chollet)

    Book Cover Watermark PDF Icon Read Ebook
    ×
    Size 27 MB (27,086 KB)
    Format PDF
    Downloaded 668 times
    Last checked 14 Hour ago!
    Author François Chollet
    “Book Descriptions: Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.

    In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.”

    Google Drive Logo DRIVE
    Book 1

    Hands-On Machine Learning with Scikit-Learn and TensorFlow

    ★★★★★

    Aurélien Géron

    Book 1

    Deep Learning

    ★★★★★

    Ian Goodfellow

    Book 1

    Python Data Science Handbook: Essential Tools for Working with Data

    ★★★★★

    Jake VanderPlas

    Book 1

    Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

    ★★★★★

    Chip Huyen

    Book 1

    Automate the Boring Stuff with Python: Practical Programming for Total Beginners

    ★★★★★

    Al Sweigart

    Book 1

    An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

    ★★★★★

    Gareth James

    Book 1

    Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python

    ★★★★★

    Peter Bruce

    Book 1

    Build a Large Language Model (From Scratch)

    ★★★★★

    Sebastian Raschka

    Book 1

    Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

    ★★★★★

    Sebastian Raschka

    Book 1

    Storytelling with Data: A Data Visualization Guide for Business Professionals

    ★★★★★

    Cole Nussbaumer Knaflic

    Book 1

    Python for Data Analysis

    ★★★★★

    Wes McKinney

    Book 1

    Natural Language Processing with Transformers: Building Language Applications with Hugging Face

    ★★★★★

    Lewis Tunstall

    Book 1

    The Hundred-Page Machine Learning Book

    ★★★★★

    Andriy Burkov

    Book 1

    Designing Data-Intensive Applications

    ★★★★★

    Martin Kleppmann