What is Probabilistic Machine Learning?

Probabilistic Machine Learning is a subfield that applies probabilistic methods to build machine learning models, enabling them to incorporate uncertainty and make predictions based on incomplete data. This approach encompasses various techniques like Bayesian inference and probabilistic graphical models. It's particularly useful in scenarios where one needs to reason under uncertainty, such as in risk assessment, anomaly detection, and natural language processing.

Who is the target audience for this book?

The target audience for 'Probabilistic Machine Learning: An Introduction' includes students, researchers, and professionals in fields such as computer science, data science, and statistics. The book is designed for those with a foundational understanding of machine learning concepts and aims to provide deeper insights into probabilistic frameworks. It serves as an excellent resource for graduate-level courses or self-study, guiding readers through complex concepts with clarity.

What topics does this book cover?

This book covers a range of essential topics including Bayesian methods, Markov Chain Monte Carlo techniques, and variational inference. It delves into model evaluation, overfitting, and inference, along with practical applications. The structured approach allows readers to build a robust understanding, with case studies that illustrate real-world use cases. These aspects make it a valuable reference for anyone looking to enhance their expertise in machine learning.

Is prior knowledge in statistics necessary to understand this book?

While prior knowledge of statistics can be beneficial, 'Probabilistic Machine Learning: An Introduction' is structured to be accessible to readers with foundational knowledge in related fields. It introduces key concepts gradually and provides intuitive explanations. Those without a strong statistics background can still learn effectively, especially if they are willing to engage with supplementary resources. This makes it suitable for a broader audience eager to delve into probabilistic methods.

Can this book be useful for practical applications?

Absolutely! This book not only discusses theoretical foundations but also emphasizes practical applications through real-world examples. Readers can learn how to apply probabilistic models to various domains, such as finance, healthcare, and AI. For instance, probabilistic methods can be used to predict stock market trends or to assess patient risk in medical settings, making this knowledge highly applicable across multiple fields.

What makes this book different from other machine learning books?

The unique aspect of 'Probabilistic Machine Learning: An Introduction' is its focus on integrating probability theory with machine learning practices. Unlike other texts that may emphasize deterministic models, this book guides readers through the nuances of uncertainty and probabilistic reasoning. This critical perspective allows practitioners to better handle real-world challenges like missing data or noisy inputs, setting it apart from traditional resources.

Are there exercises and examples included in the book?

Yes, the book includes numerous exercises and examples that are designed to reinforce the concepts discussed in each chapter. These practical exercises provide readers with the opportunity to apply what they learn and get hands-on experience with probabilistic models. This interactive learning approach is especially beneficial for those who wish to deepen their understanding and gain confidence in applying these techniques.

What prerequisites should I have before reading this book?

Before diving into 'Probabilistic Machine Learning: An Introduction', it's suggested to have a basic understanding of linear algebra, calculus, and introductory machine learning concepts. Familiarity with programming can also enhance your experience, as many practical examples involve coding implementations. These prerequisites help readers navigate through the mathematical foundations and better grasp the application of probabilistic models.

How does this book approach complex topics?

The book approaches complex topics by breaking them into manageable sections and providing clear explanations accompanied by visual aids, such as diagrams and charts. This instructional design facilitates understanding by progressively building on earlier knowledge, allowing readers to grasp advanced concepts like Bayesian networks and graphical models in a structured manner. This method is particularly helpful for readers who may be intimidated by the complexity of the subject matter.

Probabilistic Machine Learning: An Introduction está disponível para compras online em Portugal?

Sim, na Ubuy Portugal este produto está disponível para você comprar a um preço razoável.. O Probabilistic Machine Learning: An Introduction não está disponível localmente, mas você pode confiar em nós com nossos serviços de remessa expressa.

Quanto tempo leva para receber o produto após fazer o pedido?

O tempo de entrega do seu produto encomendado varia de acordo com o que você pediu e o método de envio que você escolheu.. O tempo estimado de entrega é mencionado durante o processo de checkout, portanto, fique despreocupado ao fazer compras.

Ver Original

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

This book offers a detailed and up-to-date introduction to machine learning through the unifying lens of probabilistic modeling and Bayesian decision theory.

Artigo n.º: 40164543

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

Q: Where can I buy Probabilistic Machine Learning: An Introduction in Portugal?

You can purchase 'Probabilistic Machine Learning: An Introduction' on Ubuy, a reliable online platform that offers a wide selection of books. Ubuy is known for providing a seamless shopping experience, making it convenient to find and buy educational materials. Simply visit their website and search for the book title to access the product and make your purchase with confidence.

88% of respondents would recommend this to a friend

Artigo n.º: 40164543

€ 111

Detalhes do Preço

Excluindo custos de envio e alfandegários ( Os custos de envio e alfandegários serão calculados na finalização da compra )

^{*Todos os artigos serão importados de EUA}

Disponibilidade : Em stock

Importado da loja USA

Qtd.:

Encomende já e receba por volta de Sexta-Feira, Outubro 09

Transação segura

Os nossos principais Parceiros Logísticos

This book offers a detailed and up-to-date introduction to machine learning through the unifying lens of probabilistic modeling and Bayesian decision theory.

Garantia U-Care:

Nenhuma

Selecione um plano

Fast
Shipping

Devolução
gratuita^*

Embalagem Segura

Produtos 100% Originais

Certificação PCI DSS

Certificação ISO 27001

Note: Step Down Voltage Transformer required for using electronics products of EUA store (110-120). Recommended power converters COMPRAR AGORA.

O que se Destaca

Comprehensive Coverage

This book offers an extensive exploration of probabilistic methods in machine learning, catering to both beginners and advanced practitioners, making it a valuable resource in the field.

Practical Applications

The content integrates theory with practical examples, enabling readers to apply probabilistic concepts in real-world scenarios, enhancing their understanding and skill set in machine learning.

Adaptive Learning

Utilizing the Adaptive Computation approach, this book adapts to varying skill levels, ensuring that learners can progress at their own pace while gaining profound insights into machine learning techniques.

Detalhes do produto

Comprehensive introduction to machine learning presented through the lens of probabilistic modeling and Bayesian decision theory
Covers mathematical background, basic supervised learning, and advanced topics including transfer learning and unsupervised learning
Includes end-of-chapter exercises for practical application
Completely new book reflecting the latest developments in the field, particularly deep learning
Accompanied by online Python code for reproducing figures and practical implementation
Part of a series, with a sequel covering more advanced topics in the same probabilistic approach

Publisher	The MIT Press
Publication date	March 1, 2022
Language	English
Print length	864 pages
ISBN-10	0262046822
ISBN-13	978-0262046824
Item Weight	3.31 pounds (1.5 kg)
Dimensions	8.39 x 1.3 x 9.25 inches (21.3 x 3.3 x 23.5 cm)

Quem Deverá Comprar?

Students in AI
Ideal for undergraduate and graduate students seeking foundational knowledge in probabilistic methods for machine learning.
Data Scientists
Beneficial for data scientists who want to expand their expertise in probabilistic approaches to data modeling and analysis.
Research Professionals
Suitable for researchers looking for comprehensive insights and methodologies related to probabilistic machine learning techniques.

Beginners in Programming
Not ideal for those without programming experience as the content may require prior coding skills and mathematical understanding.

DESCRIÇÃO DO PRODUTO

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

Tem alguma Dúvida? Converse connosco

Perguntas e respostas do cliente

Pergunta: Como comprar Probabilistic Machine Learning: An Introduction online na Ubuy?

Resposta: É fácil comprar Probabilistic Machine Learning: An Introduction online na Ubuy.. Você só precisa procurar o produto, escolher a forma de envio na hora de finalizar a compra e receber no seu endereço.
Pergunta: Probabilistic Machine Learning: An Introduction está disponível para compras online em Portugal?

Resposta: Sim, na Ubuy Portugal este produto está disponível para você comprar a um preço razoável.. O Probabilistic Machine Learning: An Introduction não está disponível localmente, mas você pode confiar em nós com nossos serviços de remessa expressa.
Pergunta: Quanto tempo leva para receber o produto após fazer o pedido?

Resposta: O tempo de entrega do seu produto encomendado varia de acordo com o que você pediu e o método de envio que você escolheu.. O tempo estimado de entrega é mencionado durante o processo de checkout, portanto, fique despreocupado ao fazer compras.

Intelligence & Semantics Editorial Review

Nenhuma análise editorial encontrada

Avaliações e Classificações dos Clientes

5.0

1 classificações de clientes

5 Estrela

100%
4 Estrela

0%
3 Estrela

0%
2 Estrela

0%
1 Estrela

0%

Avaliar este produto

Partilhe as suas ideias com outros clientes

Histórico de preços do produto

Informação importante

Limitações: para produtos expedidos internacionalmente, tenha em atenção que qualquer garantia do fabricante pode não ser válida; opções de serviço do fabricante podem não estar disponíveis; manuais de produtos, instruções e avisos de segurança podem não estar nas línguas do país de destino; os produtos (e materiais que o acompanham) pode não ter sido concebido em conformidade com as normas, especificações e requisitos de rotulagem do país de destino; e os produtos podem não estar em conformidade com a voltagem e outras normas elétricas do país de destino (requerendo assim o uso de um adaptador ou conversor caso seja apropriado). O destinatário é responsável por garantir que o produto pode ser legalmente importado para o país de destino. Quando encomenda à Ubuy ou aos seus afiliados, o destinatário é o importador de registo e deve estar em conformidade com todas as leis e regulamentos do país de destino.
Nem todos os produtos listados na Ubuy estão à venda, uma vez que a Ubuy é um motor de busca global. Os produtos estão sujeitos a leis de exportação/comércio.

€ 111

Encomende já e receba por volta de Sexta-Feira, Outubro 09

Qtd.:

Transação segura

Em conformidade com a norma PCI DSS e com certificação ISO 27001:2022, com pagamentos encriptados e proteção total do comprador em todas as encomendas.

Os nossos principais Parceiros Logísticos

Entrega internacional mais rápida

Recursos e benefícios

Comprehensive introduction to machine learning and deep learning.
Focus on probabilistic modeling and Bayesian decision theory.
Covers essential mathematical backgrounds, including linear algebra and optimization.
Includes practical exercises at the end of each chapter for real-world application.
Accompanied by online Python code for nearly all figures, enhancing learning.
Prepares students for advanced topics in machine learning with a sequel.

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns ^*, and secure packaging on every order.

Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)

€ 111

Fast Shipping

Devolução gratuita*

Embalagem Segura

Produtos 100% Originais

Certificação PCI DSS

Certificação ISO 27001

O que se Destaca

Detalhes do produto

Quem Deverá Comprar?

DESCRIÇÃO DO PRODUTO

Perguntas e respostas do cliente

Intelligence & Semantics Editorial Review

Avaliações e Classificações dos Clientes

Avaliar este produto

Histórico de preços do produto

Informação importante

€ 111

Recursos e benefícios

Ubuy Assurance

Fast
Shipping

Devolução
gratuita^*