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Engineers Build Models

Models play an important role in engineering. Models are used to test and improve designs. Readers w;...

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Testing with Models

Engineers build models to help them test how well their solutions will work. Read about how testing small-sized models helps them spot;

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Haciendo Pruebas Con Modelos (Testing with Models)

"Engineers build models to help them test how well their solutions will work. Read about how testing small-sized models helps them spot;

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Building And Solving Mathematical Programming Models In Engineering And Science

Modeling is one of the most appealing areas in engineering and applied sciences. Engineers need to build models to solve real life problems;

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Deploy Machine Learning Models to Production

Build and deploy machine learning and deep learning models in production with end-to-end examples. This book begins with a focus on the;

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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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Building Machine Learning Pipelines Automating Model Life Cycles with Tensorflow

these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended;

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Forecasting Time Series Data with Facebook Prophet

regressors using Python Key Features Learn how to use the open-source forecasting tool Facebook Prophet to improve your forecasts Build a;

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PyTorch Deep Learning Hands-On

Implement key deep learning methods in PyTorch: CNNs, GANs, RNNs, reinforcement learning, and more Build deep learning workflows and take deep;

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Caffe2 Quick Start Guide

Build and train scalable neural network models on various platforms by leveraging the power of Caffe2 Key Features Migrate models trained;

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Python Advanced Guide to Artificial Intelligence: Advanced Guide to Artificial Intelligence: Expert machine learning systems and intelligent agents us

supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image;

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Hands-On Deep Learning with Go

Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key Features Gain a practical understanding;

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Software Testing and Quality Assurance

models for requirements, defects, test cases, and test results Process models for units, integration, system, and acceptance testing How to build;

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PyTorch Recipes

Learn how to use PyTorch to build neural network models using code snippets updated for this second edition. This book includes new;

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Learn Amazon SageMaker

Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker;

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Learn Amazon SageMaker

Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker's;

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Finite Element Analysis and Design of Metal Structures

concepts and procedures needed to build accurate numerical models without using expensive laboratory testing methods. Professionals and researchers;

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Building Machine Learning Powered Applications Going from Idea to Product

Learn the skills necessary to design, build, and deploy applications powered by machine learning (ML). Through the course of this hands-on;

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Practical Applications of Bayesian Reliability

Demonstrates how to solve reliability problems using practical applications of Bayesian models T;...

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Behavioral Modelling and Predistortion of Wideband Wireless Transmitters

Covers theoretical and practical aspects related to the behavioral modelling and predistortion of wi;...

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Programming with TensorFlow

This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train;

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Practical Weak Supervision

Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build;

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How to Implement Market Models Using VBA

includes chapters on VBA fundamentals and essential mathematical techniques, helping readers master the numerical methods to build an algorithm;

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Generative Deep Learning Teaching Machines to Paint, Write, Compose and Play

models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build;

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Introducing MLOps How to Scale Machine Learning in the Enterprise

numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build;

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Learn PySpark

Leverage machine and deep learning models to build applications on real-time data using PySpark. This book is perfect for those who want to;

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