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Deep Learning mit TensorFlow, Keras und TensorFlow.js

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Deep Learning with TensorFlow 2 and Keras

Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key;

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Machine Learning mit Python und Keras, TensorFlow 2 und Scikit-learn

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Beginning Deep Learning with TensorFlow

TensorFlow 2 and Keras.;

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Step by Step Tutorials on Deep Learning Using Scikit-Learn, Keras, and Tensorflow with Python GUI

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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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TensorFlow für Dummies

wenig A1/4ber neuronale Netze und Deep Learning wissen. Sie erfahren, auf welchen Prinzipien TensorFlow basiert und wie Sie mit TensorFlow;

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Hands-On Deep Learning for Images with TensorFlow

all the concepts of deep learning and their implementation with TensorFlow and Keras. What you will learn Build machine learning models;

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What's New in TensorFlow 2.0

TensorFlow Keras APIs, eager execution, and efficient distribution strategies that help you to run your machine learning models on multiple GPUs and;

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Deep Learning Projects Using TensorFlow 2

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will;

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Advanced Applied Deep Learning

-advanced Python and machine learning know-how. Additionally, intermediate knowledge of Keras and TensorFlow is expected.;

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Beginning Deep Learning with TensorFlow

TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands;

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TensorFlow 2.0 Quick Start Guide

your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced;

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Deep Learning Projects Using TensorFlow 2

Work through engaging and practical deep learning projects using TensorFlow 2.0.;

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TensorFlow Deep Learning Projects

Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios Key Features Build efficient deep;

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Machine Learning Using TensorFlow Cookbook

learning library, TensorFlow. This cookbook covers the fundamentals of the TensorFlow library, including variables, matrices, and various data;

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Learn TensorFlow 2.0

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with;

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Learn TensorFlow 2.0

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing;

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Reinforcement Learning

learning and AI Work with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using Python Who This Book;

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Pro Deep Learning with TensorFlow

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition;

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TensorFlow 2 Reinforcement Learning Cookbook

deep reinforcement learning agents from scratch using the all-new TensorFlow 2.x and Keras API Implement state-of-the-art deep reinforcement;

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Deep Learning with Applications Using Python

learning frameworks such as TensorFlow, Keras, and scikit-learn. Use face recognition and face detection capabilities Create speech-to-text;

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Advanced Deep Learning with Keras

libraries. A new second edition, updated for 2020 and featuring TensorFlow 2 and coverage of unsupervised learning using mutual information, object;

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TensorFlow 1.x Deep Learning Cookbook

and implement tricky neural networks using Google's TensorFlow 1.x * An easy-to-follow guide that lets you explore reinforcement 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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Artificial Intelligence, Machine Learning, and Deep Learning

learning architectures such as CNNs, RNNs,LSTMs, and auto encoders. Keras-based code samples are included to supplementthe theoretical discussion;

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Python 3 for Machine Learning

related to machine learning Includes separate appendices for regular expressions, Keras, and TensorFlow 2;

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