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Exibindo: 1 - 44 de 537 resultados
Projetando sistemas de Machine Learning
Projetando Sistemas de Machine Learning Os sistemas de Machine Learning (ML) são complexos e únicos. Complexos porque são compostos de muitos componentes diferentes e envolvem muitas partes interessadas diferentes. Únicos porque são dependentes de dados, e esses dados variam muito de um caso de uso para outro. Neste livro, você aprenderá uma abordagem holística para projetar sistemas de ML que sej...
2024
Machine Learning with R
<p><strong>R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.</strong></p><p><br></p><p><strong>Key Features:</strong></p><ul><li>Harness the power of R for statistical computing and data science</li><li>Use R to apply common machine ...
2013
Técnicas de machine learning
O desenvolvimento de modelos de análise aplicados à realidade empresarial se tornou competência crítica em todos os setores de atividade econômica e os profissionais enfrentam duas questões. Como geraremos valor a partir dos dados? Como usaremos corretamente os métodos de análise? Existe um crescente arsenal de técnicas de Machine Learning, provocando efeitos colaterais indesejáveis, como a adoção...
Python para Data Science
A era da informação trouxe consigo uma avalanche nunca vista na criação de entendimento digital. O acesso e a interpretação desses dados tornaram-se um diferencial estratégico para empresas e também para governos, e podem dar suporte a estudos em várias áreas, como Economia e Política, passando pelas Ciências Sociais. É nesse contexto que as ferramentas necessárias para o tratamento desses dados ...
2023
Big data and machine learning in quantitative investment
Big data and machine learning in quantitative investment
2019
Data analysis, machine learning and applications
Data analysis, machine learning and applications
2008
Livro iot streams for data-driven predictive maintenance and iot, edge, and mobile for embedded machine learning
Livro iot streams for data-driven predictive maintenance and iot, edge, and mobile for embedded machine learning
2021
Livro machine learning for kids (tinker toddlers)
Livro machine learning for kids (tinker toddlers)
2019
Machine learning and data mining in pattern recognition
Machine learning and data mining in pattern recognition
1999
Machine learning methods in the environmental sciences
Machine learning methods in the environmental sciences
2009
Machine Learning on Geographical Data Using Python
Chapter 1: Introduction to Geodata<div>Chapter Goal: Presenting what geodata is, how to represent it, its difficulties</div><div>No of pages 20</div><div>Sub -Topics</div><div>1. Geodata definitions</div><div>2. Geographical Information Systems and common tools</div><div>3. Standard formats of geographical data</div><div>4. Overview of Python tools for geodata</div><div><br></div><div>Chapte...
2022
Machine Learning for Hackers
<DIV><P>If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional m...
2012
Probability for statistics and machine learning
Probability for statistics and machine learning
2011
Statistical and machine learning approaches for network ana
Statistical and machine learning approaches for network ana
2012
Building Machine Learning Systems with Python - Third Edition
<p><strong style="color: rgba(68, 68, 68, 1)">Build intelligent end-to-end machine learning systems with Python</strong></p><p><strong>Key Features</strong></p><ul><li>Use scikit-learn and TensorFlow to train your machine learning models</li><li>Implement popular supervised and unsupervised machine learning algorithms in Python</li><li>Discover best practices for building production-grade machine ...
2018
Graph Machine Learning
<p><strong>Build machine learning algorithms using graph data and efficiently exploit topological information within your models</strong></p><p><br></p><p><strong>Key Features:</strong></p><ul><li>Implement machine learning techniques and algorithms in graph data</li><li>Identify the relationship between nodes in order to make better business decisions</li><li>Apply graph-based machine learning me...
2021
Hands-On Machine Learning with C++
<p><strong>Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasets</strong></p><p><strong>Key Features</strong></p> <ul> <li>Become familiar with data processing, performance measuring, and model selection using various C++ libraries</li> <li>Impleme...
2020
Interpretable Machine Learning with Python
<p><strong>Understand the key aspects and challenges of machine learning interpretability, learn how to overcome them with interpretation methods, and leverage them to build fairer, safer, and more reliable models</strong></p><p><br></p><p><strong>Key Features:</strong></p><ul><li>Learn how to extract easy-to-understand insights from any machine learning model</li><li>Become well-versed with inter...
2021
Machine Learning Engineering with Python
<p><strong>Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments</strong></p><p><br></p><p><strong>Key Features:</strong></p><ul><li>Explore hyperparameter optimization and model management tools</li><li>Learn object-oriented programming and functional programming in Python to build your own ML libraries and p...
2021
Machine Learning Algorithms - Second Edition
<p><strong>An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms</strong></p> <p><strong>Key Features</strong></p> <ul><li>Explore statistics and complex mathematics for data-intensive applications </li> <li>Discover new developments in EM algorithm, PCA, and bayesian regression </li> <li>Study patterns and make predictions across...
2018
Machine learning concepts with python and the jupyter noteb
Machine learning concepts with python and the jupyter noteb
2020
Mastering Machine Learning Algorithms - Second Edition
Mastering Machine Learning Algorithms - Second Edition
2020
Pattern Recognition and Machine Learning
<P>This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition ...
2016