What topics are covered in the book 'Modern Time Series Forecasting with Python'?

The book covers a wide range of topics including foundational concepts of time series analysis, various machine learning algorithms, and deep learning techniques applied to forecasting using Python, PyTorch, and pandas. Each chapter dives into practical applications, making it ideal for both beginners and advanced practitioners. The hands-on approach facilitates a thorough understanding of model development, evaluation, and deployment. For instance, you will learn how to apply LSTM networks to predict stock prices or analyze seasonal trends in sales data.

Who is the target audience for this book?

This book is tailored for data scientists, analysts, and developers who possess a foundational knowledge of Python and want to delve into time series forecasting. It's also great for business professionals looking to leverage data-driven decision-making through predictive analytics. With practical examples and accessible explanations, individuals seeking to enhance their skills in machine learning and deep learning will find it particularly beneficial. For instance, a marketing analyst can use the techniques outlined to predict sales trends based on historical customer behavior.

Does the book provide hands-on projects?

Yes, the book includes several hands-on projects that allow readers to apply what they've learned in practical scenarios. Each project is designed to reinforce the concepts of time series forecasting and machine learning techniques using real-world datasets. This is crucial for developing a deeper understanding of the subject. For example, you might work on a project that involves predicting the weather or stock market fluctuations, giving you direct experience with the tools and methods discussed in the book.

Is prior knowledge of data science required to understand the content?

While a basic understanding of Python programming and data analysis is beneficial, the book is structured to cater to various skill levels. It starts with the foundational principles of time series analysis and gradually progresses to complex topics. This ensures that readers with limited experience can grasp the essential concepts and apply them effectively. For instance, if you have worked with data in simple projects before, you will be able to adapt and implement advanced techniques showcased in the book.

What are some practical applications of time series forecasting discussed in the book?

The book explores multiple practical applications of time series forecasting across various industries. Examples include stock price predictions, energy consumption forecasting, sales forecasts, and demand planning for inventory management. By learning the methodologies, readers can implement solutions in their respective fields to optimize operations and inform strategies. For example, retail businesses can use forecasting to manage inventory levels during peak seasons effectively.

What programming libraries will I learn to use in this book?

This book emphasizes the use of popular Python libraries such as pandas for data manipulation, PyTorch for deep learning applications, and various machine learning frameworks. You will learn how to leverage these libraries to analyze time series data effectively and develop predictive models. By mastering these tools, you will be equipped to handle different datasets and create robust forecasting systems. For instance, using pandas, you can easily preprocess your data, while PyTorch will allow you to build and train complex neural networks.

Can this book help me prepare for a data science interview?

Absolutely! The book prepares you with key concepts and practical skills that are often relevant in data science interviews, especially those focusing on time series analysis and forecasting. It provides a comprehensive understanding of both theoretical and practical aspects, enabling you to discuss relevant projects and techniques confidently. For instance, you could explain your approach to building a forecasting model using LSTM networks, showcasing your technical knowledge and hands-on experience.

What is the difference between machine learning and deep learning in the context of time series forecasting?

Machine learning refers to traditional algorithms, while deep learning involves neural networks that can capture complex patterns in data. In time series forecasting, machine learning techniques such as ARIMA might be used for simpler datasets, whereas deep learning models like LSTMs can manage large datasets with intricate patterns. The book explores both methodologies, demonstrating when to apply each technique effectively. This is particularly useful when deciding how to approach forecasting tasks in fields like finance or climate science.

Are there any prerequisites for this book?

While there are no strict prerequisites, a fundamental understanding of Python and basic statistical concepts is recommended for optimal comprehension. Familiarity with data analysis concepts will also be advantageous. This prior knowledge will facilitate your learning process as you engage with the tools and methods introduced throughout the book. For example, if you already have experience with Python libraries like NumPy and pandas, you will find it easier to follow along with the practical examples provided.

Where can I buy 'Modern Time Series Forecasting with Python' in São Tomé and Príncipe?

You can purchase 'Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas 2nd ed.' from Ubuy in São Tomé and Príncipe. Ubuy offers an extensive selection of books and other products, ensuring a smooth shopping experience. You can easily navigate their platform to find this title and other related resources to support your learning in time series analysis and forecasting.

Como comprar Modern Time Series Forecasting with Python: online na Ubuy?

É fácil comprar Modern Time Series Forecasting with Python: 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.

Modern Time Series Forecasting with Python: está disponível para compras online em São Tomé and Príncipe?

Sim, na Ubuy São Tomé and Príncipe este produto está disponível para você comprar a um preço razoável.. O Modern Time Series Forecasting with Python: 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

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models.

Artigo n.º: 99291537

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

87% of respondents would recommend this to a friend

Artigo n.º: 99291537

STD 1428650

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 Sábado, Outubro 17

Transação segura

Os nossos principais Parceiros Logísticos

This practical, hands-on guide empowers you to build and deploy powerful time series forecasting models.

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 Learning

Covers both machine learning and deep learning techniques, offering a deep dive into time series analysis, ensuring learners acquire industry-relevant skills for real-world applications.

Hands-on Approach

Utilizes PyTorch and pandas for practical coding examples, empowering readers to implement learned concepts effectively, making it suitable for both beginners and seasoned practitioners.

Updated Content

The 2nd edition includes the latest advancements in technology and methodologies, providing readers with current insights that enhance their understanding and execution of modern forecasting techniques.

Detalhes do produto

Publisher	Packt Publishing
Publication date	October 31, 2024
Edition	2nd ed.
Language	English
Print length	658 pages
ISBN-10	1835883184
ISBN-13	978-1835883181
Item Weight	2.46 pounds (1.12 kg)
Dimensions	7.5 x 1.49 x 9.25 inches (19.1 x 3.8 x 23.5 cm)

Quem Deverá Comprar?

Data Scientists
Ideal for data scientists wanting to enhance their time series analysis skills using Python frameworks like PyTorch.
Machine Learning Engineers
Suitable for ML engineers seeking industry-ready techniques to implement sophisticated time series forecasting models.
Students & Researchers
Beneficial for students and researchers studying time series analysis with practical, hands-on examples in Python.

Beginners
Not suitable for absolute beginners without prior knowledge of Python, machine learning concepts, or time series basics.

DESCRIÇÃO DO PRODUTO

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

Tem alguma Dúvida? Converse connosco

Perguntas e respostas do cliente

Pergunta: Como comprar Modern Time Series Forecasting with Python: online na Ubuy?

Resposta: É fácil comprar Modern Time Series Forecasting with Python: 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: Modern Time Series Forecasting with Python: está disponível para compras online em São Tomé and Príncipe?

Resposta: Sim, na Ubuy São Tomé and Príncipe este produto está disponível para você comprar a um preço razoável.. O Modern Time Series Forecasting with Python: 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.

Machine Theory Editorial Review

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas provides an extensive understanding of time series analysis, essential for data scientists attempting to leverage both foundational and advanced methodologies. This book stands out with its structured approach, guiding readers from basic concepts to machine learning and deep learning applications specific to forecasting. Readers have praised the clear explanations and layered information, making it accessible and practical for real-world applications. Topics such as the mathematical foundations, algorithm developments, and the integration of deep learning in forecasting illustrate its comprehensive outlook, ensuring that even those new to the field can gain valuable insights and tools from this resource.

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

Prós

Thorough coverage of foundational and advanced topics
Practical applications with real-world examples
Clear structure enhances learning experience
Great resource for both beginners and experts
Includes coding samples for hands-on practice

Contras

Content may feel lengthy for casual readers

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.

STD 1428650

Encomende já e receba por volta de Sábado, Outubro 17

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

Learn traditional and advanced techniques for time series forecasting.
Hands-on practical examples to improve forecasting accuracy.
Includes free eBook with print or Kindle purchase.
Covers deep learning models including RNNs and transformers.
Ideal for professionals and students in various industries.
New edition features enhancements in transformer architectures and probabilistic forecasting.

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.

Modern Time Series Forecasting with Python: Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas

STD 1428650

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

Machine Theory Editorial Review

Avaliações e Classificações dos Clientes

Avaliar este produto

Prós

Contras

Histórico de preços do produto

Informação importante

STD 1428650

Recursos e benefícios

Ubuy Assurance

Fast
Shipping

Devolução
gratuita^*