Practical deep learning for cloud, mobile, and edge : Real-world AI and computer-vision projects using python, keras, and tensorflow / Anirudh Koul, Siddha Ganju, and Meher Kasam.
Material type:
- 9781492034865
- QA76.76.A65 .K68 2019
Item type | Current library | Collection | Call number | Copy number | Status | Barcode | |
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Zetech Library - Mang'u Campus General Stacks | Non-fiction | QA76.76.A65 .K68 2019 (Browse shelf(Opens below)) | C.2 | Available | Z009651 | |
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Zetech Library - Mang'u Campus General Stacks | Non-fiction | QA76.76.A65 .K68 2019 (Browse shelf(Opens below)) | C.1 | Available | Z009650 |
Includes index.
Exploring the landscape of Artificial Intelligence -- What's in the picture: Image classification with Keras -- Cats versus dogs: Transfer learning in 30 lines with Keras -- Building a reverse image search engine: Understanding embeddings -- From Novice to master predictor: Maximizing convolutional neural network accuracy -- Maximizing speed and performance of tensorflow: A handy checklist -- Practical tools, tips, and tricks -- Cloud APIs for computer vision: Up and running in 15 minutes -- Scalable inference serving on cloud with tensorflow serving and Kubeflow -- AI in the browser with tensorflow.Js and ml5.Js -- Real-time object classification on iOS with core ML -- Not hotdog on iOS with core ML and create ML -- Shazam for food: Developing android Apps with tensorflow lite and ML kit -- Building the purrfect Cat locator App with tensorflow object detection API -- Becoming a maker: Exploring embedded AI at the edge -- Simulating a self-driving car using end-to-end deep learning with Keras -- Building an autonomous car in under an hour: Reinforcement learning with AWS deepracer -- Appendix: A crash course in convolutional neutral networks.
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