Download Deep Learning with Python by Francois Chollet (.MP3)

Deep Learning with Python by Francois Chollet, Narrated by Mark Thomas
Requirements: .MP3 reader, 272.6MB, Length: 9 hrs and 55 mins, Unabridged Audiobook, Chaptered
Overview: Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this audiobook builds your understanding through intuitive explanations and practical examples. You’ll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you’ll have the knowledge and hands-on skills to apply deep learning in your own projects.

Deep learning from first principles

Setting up your own deep-learning environment

Image-classification models

Deep learning for text and sequences

Neural style transfer, text generation, and image generation

Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn’t beat a serious Go player, to defeating a world champion. Behind this progress is deep learning – a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.

François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
Genre: Audiobooks > Non-Fiction

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