Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow

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"O'Reilly Media, Inc.", Oct 14, 2019 - Computers - 586 pages

Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach.

Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.

  • Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite
  • Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral
  • Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies
  • Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning
  • Use transfer learning to train models in minutes
  • Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
 

Selected pages

Contents

Section 1
Section 2
Section 3
Section 4
Section 5
Section 6
Section 7
Section 8
Section 15
Section 16
Section 17
Section 18
Section 19
Section 20
Section 21
Section 22

Section 9
Section 10
Section 11
Section 12
Section 13
Section 14
Section 23
Section 24
Section 25
Section 26
Section 27
Copyright

Other editions - View all

Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI ...
Anirudh Koul,Siddha Ganju,Meher Kasam
Limited preview - 2019
Practical Deep Learning for Cloud and Mobile: Hands-On Computer Vision ...
Anirudh Koul,Siddha Ganju,Meher Kasam
No preview available - 2019

Common terms and phrases

A/B testing accuracy Additionally algorithm Android architecture augmentation autonomous car AWS DeepRacer batch benchmarks bounding box browser build Chapter classifier computer vision convolutional Core ML Create ML custom deep learning deploy device eager execution embeddings example experiment explore Figure Firebase FPGA frameworks GitHub Google Cloud hardware heatmap http://PracticalDeepLearning.ai hyperparameters inference input install iPhone Jetson Nano Keras KubeFlow label layers learning models learning rate load look machine learning Microsoft mobile MobileNet multiple neural network NVIDIA object detection optimal options output parameters performance pipeline pixels predictions pretrained model Python quantization Raspberry Pi Real-Time Object real-world recognition reinforcement learning resizing reward function scenarios similar smartphones speed Sudoku task TensorBoard TensorFlow Lite track transfer learning tuning upload users visual Xcode YouTube

About the author (2019)

Anirudh Koul is the Head of AI & Research at Aira, and was previously at Microsoft AI & Research where he founded Seeing AI - the defacto app used by the blind community worldwide. With features shipped to about a billion people, he brings over a decade of production-oriented applied research experience on petabyte-scale datasets. He has been transforming ideas to reality using AI for Augmented Reality, Robotics, Speech, Productivity as well as building tools for people with disabilities. His work, which the IEEE has called ‘life changing’, has been honored by CES, FCC, Cannes Lions, American Council of the Blind, showcased at events by UN, White House, House of Lords, World Economic Forum, TEDx, on Netflix, National Geographic, and applauded by world leaders including Justin Trudeau and Theresa May.

Siddha Ganju, who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. Previously at Deep Vision, she developed deep learning models for resource constraint edge devices. A graduate from Carnegie Mellon University, her prior work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN's petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS. Serving as an AI domain expert, she has also been guiding teams at NASA as well as featured as a jury member in several international tech competitions.

Meher is a seasoned software developer with apps used by tens of millions of users every day. Currently at Square, and previously at Microsoft, he shipped features for a range of apps, from Square’s Point of Sale to the Bing app. He was the mobile development lead for Microsoft’s Seeing AI app, which has received widespread recognition and awards from Mobile World Congress, CES, FCC, American Council of the Blind to name a few. A hacker at heart with a flair for fast prototyping, he has won close to two dozen hackathons and converted them to features shipped in widely-used products. He also serves as a judge of international competitions including Global Mobile Awards, Edison Awards.

Bibliographic information

QR code for Practical Deep Learning for Cloud, Mobile, and Edge
TitlePractical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow
AuthorsAnirudh Koul, Siddha Ganju, Meher Kasam
Publisher"O'Reilly Media, Inc.", 2019
ISBN1492034819, 9781492034810
Length586 pages
Subjects ›  › 

Computers / Artificial Intelligence / Computer Vision & Pattern Recognition
Computers / Artificial Intelligence / General
Computers / Artificial Intelligence / Natural Language Processing
Computers / Business & Productivity Software / General
Computers / Data Science / Neural Networks
Computers / Distributed Systems / Cloud Computing
Computers / Hardware / Cell Phones & Devices
Computers / Image Processing
Computers / Machine Theory
  
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