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

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

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Deep Learning with TensorFlow 2 and Keras

2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to;

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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author;

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Python for Probability, Statistics, and Machine Learning

, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance;

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Python for Probability Statistics and Machine Learning

, Sympy, Scikit-learn, Tensorflow, and Keras are applied to simulate and visualize important machine learning concepts like the bias/variance;

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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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Python Machine Learning

Master the frameworks, models, and techniques that enable machines to 'learn' from data Use scikit-learn for machine learning and TensorFlow for;

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Deep Learning mit TensorFlow, Keras und TensorFlow.js

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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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Python for Probability, Statistics, and Machine Learning

same code on their own computers. Modern Python modules like Pandas, Sympy, Scikit-learn, Statsmodels, Scipy, Xarray, Tensorflow, and Keras;

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Applied Reinforcement Learning with Python

Implement reinforcement learning with Python Work with AI frameworks such as OpenAI Gym, Tensorflow, and Keras Deploy and train reinforcement;

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Hands-On Machine Learning with Scikit-Learn and TensorFlow

shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow-author;

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Machine Learning with Scikit-Learn and TensorFlow

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Python Machine Learning -

, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully;

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Deep Learning mit Python und Keras

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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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Beginning Anomaly Detection Using Python-Based Deep Learning

statistical and traditional machine learning methods for anomaly detection using Scikit-Learn in Python, the book then provides an introduction to;

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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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Machine Learning with scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;

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Mastering Machine Learning Algorithms

machine learning problems Key Features Updated to include new algorithms and techniques Code updated to Python 3.8 & TensorFlow 2.x New coverage;

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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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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning

Transform games into environments using machine learning and Deep learning with Tensorflow, Keras, and Unity Key Features Learn how to;

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Python Deep Learning

. What You Will Learn * Get a practical deep dive into deep learning algorithms * Explore deep learning further with Theano, Caffe, Keras;

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HandsOn Unsupervised Learning Using Python

Python frameworks: Scikit-learn and TensorFlow using Keras. With code and hands-on examples, data scientists will identify difficult-to-find;

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Tensorflow 2

(in Python) and figures. FEATURES: Provides an overview of the most important TensorFlow programming techniques used for machine learning, deep;

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Machine Learning for Finance

reinforcement learning in Python, scikit-learn, Keras, and TensorFlow Dig deep into neural networks, examine uses of GANs and reinforcement learning;

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