Python deep learning solutions / Indra den Bakker.

[Place of publication not identified] : Packt Publishing, 2018.

English

1 online resource (1 streaming video file (1 hr., 45 min., 59 sec.))

QA76.73.P98

(OCoLC)1046057322

"Deep Learning is revolutionizing a wide range of industries. For many applications, Deep Learning has been proven to outperform humans by making faster and more accurate predictions. This course provides a top-down and bottom-up approach to demonstrating Deep Learning solutions to real-world problems in different areas. These applications include Computer Vision, Generative Adversarial Networks, and time series. This course presents technical solutions to the issues presented, along with a detailed explanation of the solutions. Furthermore, it provides a discussion on the corresponding pros and cons of implementing the proposed solution using a popular framework such as TensorFlow, PyTorch, and Keras. The course includes solutions that are related to the basic concepts of neural networks; all techniques, as well as classical network topologies, are covered. The main purpose of this video course is to provide Python programmers with a detailed list of solutions so they can apply Deep Learning to common and not-so-common scenarios."--Resource description page

Title from resource description page (Safari, viewed July 23, 2018).

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