Who is the target audience for this book?

The book is tailored for data scientists, machine learning engineers, and researchers who have a foundational understanding of deep learning. It is particularly beneficial for those who wish to enhance their knowledge of probabilistic techniques in the context of neural networks. Additionally, practitioners looking to implement these methods in real-world projects using Python, Keras, and TensorFlow will find the content highly applicable, enabling them to tackle complex data challenges.

What tools and libraries are covered in this book?

'Probabilistic Deep Learning' emphasizes the use of Python along with specific libraries such as Keras and TensorFlow Probability. Keras serves as an accessible interface for building neural networks, while TensorFlow Probability extends this with tools for probabilistic reasoning. Readers can expect to learn how to leverage these libraries for tasks such as Bayesian neural networks and variational inference, which can enhance models with uncertainty capabilities, beneficial for fields like healthcare or finance.

Are there practical examples included in the book?

Yes, the book is rich with practical examples and case studies. Each chapter typically includes code snippets and detailed explanations that guide readers through implementing techniques using real datasets. For instance, you might explore how to build a probabilistic model for predicting customer retention in e-commerce, blending theory with practical coding exercises to solidify your understanding and application of the concepts.

How does this book handle uncertainty in machine learning?

The book addresses uncertainty by integrating probabilistic modeling into deep learning paradigms. Readers will learn how to implement models that not only output predictions but also estimate the confidence of those predictions. This approach is crucial in domains such as autonomous driving or medical diagnoses, where understanding the level of uncertainty can significantly influence decision-making processes.

Is prior knowledge of deep learning necessary to read this book?

A foundational understanding of deep learning is strongly recommended for readers. Since the book covers advanced topics in probabilistic deep learning, familiarity with basic concepts such as neural networks, loss functions, and gradient descent will facilitate comprehension. However, the book often revisits key principles to help reinforce learning, making it potentially accessible for motivated beginners willing to engage with introductory materials first.

What is the relationship between probability and machine learning as discussed in the book?

The book illustrates that probability forms the bedrock of many machine learning algorithms by enabling the modeling of uncertainty and variability in data. According to the book, integrating probabilistic frameworks allows practitioners to create better decision-making systems that account for the inherent unpredictability of real-world scenarios. For example, industries such as finance and robotics face uncertainty, and utilizing these probabilistic methods can enhance predictive accuracy and reliability.

Can the concepts learned in this book be applied to real-world problems?

Absolutely! The concepts explored in 'Probabilistic Deep Learning' are highly applicable to various real-world problems, including finance, healthcare, and robotics. Understanding how to model uncertainty can lead to superior decision-making frameworks in autonomous systems or risk assessment in financial applications. By learning how to harness the power of probabilistic deep learning, professionals can tackle challenges that require nuanced insights beyond simple predictions.

What differentiates this book from other deep learning literature?

'Probabilistic Deep Learning' uniquely accomplishes the fusion of deep learning with probabilistic modeling, which is often oversimplified in traditional deep learning texts. This book provides in-depth insight into uncertainty quantification and probabilistic reasoning—areas that are becoming increasingly relevant as machine learning applications grow in complexity. The focus on TensorFlow Probability further distinguishes it, offering practical coding guidance not often found in standard resources.

Bagaimana untuk Membeli-belah Probabilistic Deep Learning: With Python, Keras and Dalam Talian Dari Ubuy?

Sangat mudah untuk membeli-belah Probabilistic Deep Learning: With Python, Keras and dalam talian daripada Ubuy.. Anda hanya perlu mencari produk, pilih kaedah penghantaran anda semasa mendaftar keluar dan hantar ke lokasi anda.

Adakah Probabilistic Deep Learning: With Python, Keras and Tersedia untuk Beli-belah Dalam Talian dalam Malaysia?

Ya, di Ubuy Malaysia produk ini tersedia untuk anda membeli-belah pada harga yang berpatutan.. Probabilistic Deep Learning: With Python, Keras and tidak tersedia secara tempatan tetapi anda boleh mempercayai kami dengan perkhidmatan penghantaran ekspres kami.

Berapa lama masa yang diperlukan untuk mendapatkan produk selepas membuat pesanan?

Masa penghantaran produk pesanan anda berbeza mengikut apa yang anda pesan dan kaedah penghantaran yang anda pilih.. Anggaran masa penghantaran dinyatakan semasa proses daftar keluar, jadi berhati-hati semasa membeli-belah.

Lihat Asal

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing.

Item #: 31410831

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition

Q: What is the focus of 'Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability'?

'Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability' primarily focuses on how to incorporate probabilistic modeling into deep learning. This approach provides a framework for better uncertainty quantification in predictions. By blending probabilistic methods with deep learning techniques, the book teaches readers how to apply these concepts using popular platforms like Keras and TensorFlow Probability. This is especially useful for scenarios where data is sparse or noisy, allowing practitioners to make more robust predictions and assess their confidence.

Q: Where can I buy 'Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition' in Malaysia?

You can purchase 'Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition' on Ubuy. Ubuy offers a wide selection of books and other products, making it a reliable choice for acquiring this title. Simply visit their website and search for the book to find it conveniently.

82% of respondents would recommend this to a friend

Item #: 31410831

MYR 313

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

^{*All items will import from AS}

Ketersediaan : Dalam stok

Diimport dari kedai USA

QTY:

Pesan sekarang dan dapatkannya lebih kurang pada Sunday, Oktober 11

Secured transaction

Our Top Logistics Partners

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing.

Waranti U-Care:

Tiada

Pilih pelan

Fast
Shipping

Free
Return^*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

Note: Step Down Voltage Transformer required for using electronics products of AS store (110-120). Recommended power converters Beli Sekarang.

What Stands Out

Comprehensive Guide

This book provides a complete introduction to probabilistic deep learning, integrating theory with practical applications, making it suitable for beginners and practitioners alike.

Hands-On Python

Utilizes Python, Keras, and TensorFlow Probability, offering practical coding examples that empower readers to implement probabilistic models in their own projects effortlessly.

Expert Insights

Written by knowledgeable authors, the book includes expert insights and best practices, ensuring readers receive reliable information to enhance their understanding and skills in this advanced field.

Maklumat produk

Publisher	Manning
Publication date	November 10, 2020
Edition	1st
Language	English
Print length	296 pages
ISBN-10	1617296074
ISBN-13	978-1617296079
Item Weight	7.4 ounces (209.79 grams)
Dimensions	7.38 x 0.3 x 9.25 inches (18.7 x 0.8 x 23.5 cm)

Who Should Buy?

Data Scientists
Perfect for data scientists seeking to incorporate probabilistic models into their analyses using Python libraries like Keras.
Machine Learning Engineers
Ideal for engineers who want to develop robust machine learning models applying probabilistic approaches in TensorFlow.
Students & Educators
Great resource for students and educators aiming to understand probabilistic deep learning concepts and their practical applications.

Beginner Programmers
Not suitable for beginners lacking foundational programming skills and understanding of machine learning principles.

PENERANGAN PRODUK

Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition

Ada sebarang Pertanyaan? Berbual dengan kami

Soalan & Jawapan Pelanggan

soalan: Bagaimana untuk Membeli-belah Probabilistic Deep Learning: With Python, Keras and Dalam Talian Dari Ubuy?

jawab: Sangat mudah untuk membeli-belah Probabilistic Deep Learning: With Python, Keras and dalam talian daripada Ubuy.. Anda hanya perlu mencari produk, pilih kaedah penghantaran anda semasa mendaftar keluar dan hantar ke lokasi anda.
soalan: Adakah Probabilistic Deep Learning: With Python, Keras and Tersedia untuk Beli-belah Dalam Talian dalam Malaysia?

jawab: Ya, di Ubuy Malaysia produk ini tersedia untuk anda membeli-belah pada harga yang berpatutan.. Probabilistic Deep Learning: With Python, Keras and tidak tersedia secara tempatan tetapi anda boleh mempercayai kami dengan perkhidmatan penghantaran ekspres kami.
soalan: Berapa lama masa yang diperlukan untuk mendapatkan produk selepas membuat pesanan?

jawab: Masa penghantaran produk pesanan anda berbeza mengikut apa yang anda pesan dan kaedah penghantaran yang anda pilih.. Anggaran masa penghantaran dinyatakan semasa proses daftar keluar, jadi berhati-hati semasa membeli-belah.

Intelligence & Semantics Editorial Review

**** "Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability" offers an intriguing journey into the realm of deep learning with a particular focus on its probabilistic elements. Customers have lauded the authors for their ability to present complex concepts in a friendly and approachable manner. Reviewers express appreciation for the clarity with which topics such as maximum likelihood estimation using neural networks, Bayesian neural networks, and normalizing flows are articulated. This unique perspective aids readers in grasping advanced ideas that might otherwise seem daunting. While the book starts with a basic introduction to deep learning and TensorFlow—a section that some readers found somewhat light—the second half delves into more substantial and useful content. However, several reviews indicate that this section still lacks the depth some readers may desire. Despite the engaging delivery of information, there is a notable concern regarding the quality of editing throughout the text. Multiple reviewers have pointed out errors on almost every page, detracting from the overall reading experience. In conclusion, while "Probabilistic Deep Learning" presents an accessible introduction to advanced concepts in the field, readers should be prepared for issues with editing and superficial coverage of some topics. **

Customer Reviews & Ratings

5.0

1 rating pelanggan

5 bintang

100%
4 bintang

0%
3 bintang

0%
2 bintang

0%
1 bintang

0%

Ulas Produk Ini

Kongsikan pandangan anda dengan pelanggan lain

Kebaikan

Friendly and approachable writing style
Clear explanations of complex concepts
Unique perspective on probabilistic deep learning techniques
Potential applications of topics discussed, particularly normalizing flows

Keburukan

Basic introductory content may not satisfy advanced readers

Product Price History

Maklumat penting

Pengehadan: Untuk produk penghantaran antarabangsa, harap maklum bahawa sebarang jaminan pengeluar mungkin tidak sah; pilihan perkhidmatan pengeluar mungkin tidak tersedia; manual produk, arahan, dan amaran keselamatan mungkin tidak dalam bahasa negara destinasi; produk-produk (dan bahan-bahan berkaitannya) mungkin tidak direka selaras dengan standard negara destinasi, spesifikasi, dan syarat pelabelan; dan produk-produk itu mungkin tidak mematuhi kepada voltan negara destinasi dan lain-lain standard elektrik (memerlukan penggunaan adaptor atau penukar aliran jika perlu). Penerima adalah bertanggungjawab untuk memastikan bahawa produk itu boleh diimport selaras dengan undang-undang negara destinasi. Apabila memesan dari Ubuy atau pihak afiliasinya, si penerima adalah merupakan pengimport dalam rekod dan mesti mematuhi kepada semua undang-undang dan peraturan negara destinasi.
Bukan semua produk yang tersenarai di Ubuy adalah untuk dijual, kerana Ubuy adalah enjin carian global. Produk-produk adalah tertakluk kepada peraturan eksport/perdagangan.

MYR 313

Pesan sekarang dan dapatkannya lebih kurang pada Sunday, Oktober 11

QTY:

Secured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners

Fastest cross-border delivery

Ciri & Faedah

Learn probabilistic deep learning to enhance accuracy
Use Python, Keras, and TensorFlow Probability for practical applications
Improve network performance with the right distribution for various data types
Discover Bayesian variants to state their own uncertainty for increased accuracy
Build deep learning applications that handle real-world data noise and uncertainty
Includes free eBook in PDF, Kindle, and ePub formats

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 Deep Learning: With Python, Keras and TensorFlow Probability 1st Edition

MYR 313

Fast Shipping

Free Return*

Secure Packaging

100% Original Products

PCI DSS Compliance

ISO 27001 Certified

What Stands Out

Maklumat produk

Who Should Buy?

PENERANGAN PRODUK

Soalan & Jawapan Pelanggan

Intelligence & Semantics Editorial Review

Customer Reviews & Ratings

Ulas Produk Ini

Kebaikan

Keburukan

Product Price History

Maklumat penting

MYR 313

Ciri & Faedah

Ubuy Assurance

Fast
Shipping

Free
Return^*