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Machine Learning with Scikit-Learn and TensorFlow

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

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TensorFlow Machine Learning Cookbook

Linear Regression techniques with TensorFlow * Learn SVMs with hands-on recipes * Implement neural networks and improve predictions * Apply;

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

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Machine Learning with scikit-learn Quick Start Guide

learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine;

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Hands-on Scikit-Learn for Machine Learning Applications

machine learning applications in the world of Python. What You'll Learn Work with simple and complex datasets common to Scikit-Learn Manipulate;

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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits

provide hands-on machine learning solutions with scikit-learn and Python toolkits. The book begins with an explanation of machine learning;

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TensorFlow For Dummies

TensorFlow on your computer Learn the fundamentals of statistical regression and neural networks Visualize the machine learning process with;

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TensorFlow Machine Learning Cookbook

-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you;

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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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Hands-on Machine Learning with Python

unsupervised learning Examine convolutional neural networks and Recurrent neural networks Get acquainted with scikit-learn and PyTorch Predict;

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Hands-on Machine Learning with Python

visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning;

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Python Machine Learning -

updates to scikit-learn. Style and Approach Python Machine Learning Second Edition takes a practical, hands-on coding approach so you can;

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Hands-On Deep Learning for Images with TensorFlow

fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;

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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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Building Machine Learning Pipelines Automating Model Life Cycles with Tensorflow

Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation;

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scikit-learn Cookbook -

deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like;

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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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Beginning Deep Learning with TensorFlow

of online learners. You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart;

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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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TensorFlow 2.0 Quick Start Guide

of machine learning and neural network TensorFlow techniques. What you will learn Use tf.Keras for fast prototyping, building, and training deep;

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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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Hands-On Machine Learning for Cybersecurity

validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning;

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Deep Learning with TensorFlow 2 and Keras

apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learn Build machine learning and deep;

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Hands-On Neural Networks with TensorFlow 2.0

familiar with the concepts and techniques required to build solutions to deep learning problems. As you advance, you'll learn how to create;

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