106,24 €
124,99 €
-15% su kodu: ENG15
Deep Learning
106,24 € 
- Išsiųsime per 12–18 d.d.
An accessible, highly-illustrated introduction to deep learning that offers visual and conceptual explanations instead of equations. Readers learn how to use key deep learning algorithms without the need for complex math.Deep Learning algorithms can start with mountains of data and measurements and turn them into useful and meaningful patterns. This book is for people with sharp minds who may lack the math background necessary to deal with equations or complex mechanics, but who nevertheless wa…
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- Autorius: Andrew Glassner
- Leidėjas: Random House LCC US
- Metai: 2021
- Puslapiai: 776
- ISBN-10: 1718500726
- ISBN-13: 9781718500723
- Formatas: 17.5 x 23.2 x 3.9 cm, minkšti viršeliai
- Kalba: Anglų
- Extra -15 % nuolaida šiai knygai su kodu: ENG15
Atsiliepimai
Aprašymas
An accessible, highly-illustrated introduction to deep learning that offers visual and conceptual explanations instead of equations. Readers learn how to use key deep learning algorithms without the need for complex math.Deep Learning algorithms can start with mountains of data and measurements and turn them into useful and meaningful patterns. This book is for people with sharp minds who may lack the math background necessary to deal with equations or complex mechanics, but who nevertheless want to understand the "how" of deep learning, and actually use these tools for themselves.
Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create "deep dream" artwork, or create new stories in the style of their favorite authors. Scientists, artists, programmers, managers, hobbyists, and intellectual adventurers of all kinds can use deep learning tools to make new discoveries and create new kinds of art and intelligent systems.
The book's friendly, informal approach to deep learning demonstrates the concepts visually. There's no math beyond the occasional multiplication and no programming experience is required. By the end of the book, readers will be equipped to understand modern deep learning systems, and anyone who wants to program and train their own deep learning networks will be able to dive into the library of their choice and start implementing with knowledge and confidence.
EXTRA 15 % nuolaida su kodu: ENG15
106,24 €
124,99 €
Išsiųsime per 12–18 d.d.
Akcija baigiasi už 3d.02:23:15
Nuolaidos kodas galioja perkant nuo 10 €. Nuolaidos nesumuojamos.
- Autorius: Andrew Glassner
- Leidėjas: Random House LCC US
- Metai: 2021
- Puslapiai: 776
- ISBN-10: 1718500726
- ISBN-13: 9781718500723
- Formatas: 17.5 x 23.2 x 3.9 cm, minkšti viršeliai
- Kalba: Anglų Anglų
An accessible, highly-illustrated introduction to deep learning that offers visual and conceptual explanations instead of equations. Readers learn how to use key deep learning algorithms without the need for complex math.
Deep Learning algorithms can start with mountains of data and measurements and turn them into useful and meaningful patterns. This book is for people with sharp minds who may lack the math background necessary to deal with equations or complex mechanics, but who nevertheless want to understand the "how" of deep learning, and actually use these tools for themselves.
Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create "deep dream" artwork, or create new stories in the style of their favorite authors. Scientists, artists, programmers, managers, hobbyists, and intellectual adventurers of all kinds can use deep learning tools to make new discoveries and create new kinds of art and intelligent systems.
The book's friendly, informal approach to deep learning demonstrates the concepts visually. There's no math beyond the occasional multiplication and no programming experience is required. By the end of the book, readers will be equipped to understand modern deep learning systems, and anyone who wants to program and train their own deep learning networks will be able to dive into the library of their choice and start implementing with knowledge and confidence.
Deep Learning algorithms can start with mountains of data and measurements and turn them into useful and meaningful patterns. This book is for people with sharp minds who may lack the math background necessary to deal with equations or complex mechanics, but who nevertheless want to understand the "how" of deep learning, and actually use these tools for themselves.
Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create "deep dream" artwork, or create new stories in the style of their favorite authors. Scientists, artists, programmers, managers, hobbyists, and intellectual adventurers of all kinds can use deep learning tools to make new discoveries and create new kinds of art and intelligent systems.
The book's friendly, informal approach to deep learning demonstrates the concepts visually. There's no math beyond the occasional multiplication and no programming experience is required. By the end of the book, readers will be equipped to understand modern deep learning systems, and anyone who wants to program and train their own deep learning networks will be able to dive into the library of their choice and start implementing with knowledge and confidence.
Atsiliepimai