Practical deep learning for cloud, mobile, and edge: real-world ai & computer-vision...
Описание
** Featured as a learning resource on the official Keras website **
Whether you're a software engineer aspiring to enter the world of deep
Explore fun projects, from Silicon Valleys Not Hotdog app to 40+ industry
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-
From Novice to Master Predictor: Maximizing Convolutional Neural Network
Tableau your data!: fast and easy visual analysis with tableau software, daniel g. murray.
Nginx cookbook: advanced recipes for high-performance load balancing 2nd edition, derek dejonghe
research into award-winning applications, Anirudh Koul, Siddha Ganju, and
Jetson Nano, and Danny Atsmon
Shazam for Food: Developing Android Apps with TensorFlow Lite and ML Kit.
Train, tune, and deploy computer vision models with Keras, TensorFlow, Core
List of Chapters.
List of Chapters
Google Coral.
Explore fun projects, from Silicon Valley's Not Hotdog app to 40+ industry
case studies.
From Novice to Master Predictor: Maximizing Convolutional Neural Network
version with reinforcement learning.
Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and.
Cloud APIs for Computer Vision: Up and Running in 15 Minutes,
debugging, and scaling to millions of users.
List of Chapters
Practical deep learning: a python-based introduction, ronald t. kneusel
What's in the Picture: Image Classification with Keras
including François Chollet
Building a Reverse Image Search Engine: Understanding Embeddings
sniper on the eastern front
Accuracy
Train, tune, and deploy computer vision models with Keras, TensorFlow, Core
Whats in the Picture: Image Classification with Keras
Python projects for beginners: a ten-week bootcamp approach to python programming, milliken connor
From Novice to Master Predictor: Maximizing Convolutional Neural Network
AI in the Browser with TensorFlow.js and ml5.js
Use transfer learning to train models in minutes
Python projects for beginners: a ten-week bootcamp approach to python programming, milliken connor
Meher Kasam guide you through the process of converting an idea into something
Jetson Nano, John Welsh
Shazam for Food: Developing Android Apps with TensorFlow Lite and ML Kit
Building the Purrfect Cat Locator App with TensorFlow Object Detection API
Building an Autonomous Car in Under an Hour: Reinforcement Learning with AWS
DeepRacer
Guest-contributed Content
Practical deep learning: a python-based introduction, ronald t. kneusel:
Sunil Mallya (Amazon
AWS DeepRacer
)
From Novice to Master Predictor: Maximizing Convolutional Neural Network (
Building the Purrfect Cat Locator App with TensorFlow Object Detection API
)
Sam Sterckval (
Edgise
)
Zaid Alyafeai (
TensorFlow.js
)
The book also features content contributed by several industry veterans
including François Chollet (
Keras
,
), Jeremy Howard (
Fast.ai
), Pete Warden (
TensorFlow Mobile
), Anima Anandkumar (
NVIDIA
), Chris Anderson (
3D Robotics
), Shanqing Cai (
TensorFlow.js
), Daniel Smilkov (
TensorFlow.js
), Cristobal Valenzuela (
ml5.js
), Daniel Shiffman (
ml5.js
), Hart Woolery (
CV 2020
), Dan Abdinoor (
Fritz
), Chitoku Yato (
NVIDIA
Jetson Nano), John Welsh (
NVIDIA
Jetson Nano), and Danny Atsmon (
Cognata
).
Також купити книгу Practical Deep Learning for Cloud, Mobile, and Edge: Real-
World AI & Computer-Vision Projects Using Python, Keras & TensorFlow, Anirudh
Koul, Siddha Ganju, Meher Kasam, more Ви можете по посиланню
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