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Practical Computer Vision Applications Using Deep Learning with CNNs

Will Learn Understand how ANNs and CNNs work Create computer vision applications and CNNs from scratch using Python Follow a deep learning;

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Learn Computer Vision Using Opencv: With Deep Learning Cnns and Rnns

Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer;

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TensorFlow 2.0 Computer Vision Cookbook

vision tasks using TensorFlow. The book begins by taking you through the basics of deep learning for computer vision, along with covering;

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A Guide to Convolutional Neural Networks for Computer Vision

, CNNs now form the crux of deep learning algorithms in computer vision. This self-contained guide will benefit those who seek to both;

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Hands-On Convolutional Neural Networks with TensorFlow

Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for;

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Mastering OpenCV 4 with Python

Create computer vision and deep learning web applications Who this book is forThis book is designed for computer vision developers, engineers;

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Hands-On Computer Vision with TensorFlow 2

. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural;

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The Deep Learning Workshop

Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;

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PyTorch Deep Learning Hands-On

major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and;

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Advanced Deep Learning with Python

networks using the Python ecosystem Key Features Get to grips with building faster and more robust deep learning architectures Investigate and;

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Deep Learning for Computer Vision

kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to;

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Deep Learning with Applications Using Python

Explore deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and;

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Machine Learning for OpenCV 4

machine learning for building intelligent computer vision applications with OpenCV 4. What you will learn Understand the core machine learning;

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Practical Deep Learning for Cloud and Mobile RealWorld AI Computer Vision Projects Using Python, Keras TensorFlow

something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, CoreML, and TensorFlow Lite;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Computer Vision Projects with PyTorch

vision algorithms and their applications using PyTorch. The book begins with the fundamentals of computer vision: convolutional neural nets;

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Python Deep Learning

computer vision and NLP Learn how a computer can navigate in complex environments with reinforcement learning Book DescriptionWith the surge;

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The Deep Learning with PyTorch Workshop

neural networks (ANNs) Handle computer vision problems with convolutional neural networks (CNNs) Perform language translation tasks using;

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The The Computer Vision Workshop

Explore the potential of deep learning techniques in computer vision applications using the Python ecosystem, and build real-time systems;

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Deep Learning with R for Beginners

Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the;

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Mastering Computer Vision with TensorFlow 2.x

analysis. You'll start with the key principles of computer vision and deep learning to build a solid foundation, before covering neural network;

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Practical Machine Learning and Image Processing

time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using;

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Practical Machine Learning and Image Processing

time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real;

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Deep Learning for Vision Systems

, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL;

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Deep Learning in Computer Vision

Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions;

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Computer Vision: Principles, Algorithms, Applications, Learning

subject. See an interview with the author explaining his approach to teaching and learning computer vision - http;

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