Beginning Deep Learning with TensorFlow: work with Keras, MNIST Data Sets, and Advanced Neural Networks
Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learn...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berkeley, CA
Apress
[2022]
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| Ausgabe: | 1st ed |
| Schlagworte: | |
| Zusammenfassung: | Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! What You'll Learn- Develop using deep learning algorithms- Build deep learning models using TensorFlow 2- Create classification systems and other, practical deep learning applicationsWho This Book Is ForStudents, programmers, and researchers with no experience in deep learning who want to build up their basic skillsets. Experienced machine learning programmers and engineers might also find value in updating their skills |
| Beschreibung: | xxiii, 713 Seiten Illustrationen, Diagramme 1116 grams |
| ISBN: | 9781484279144 |
Internformat
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| 520 | |a Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! What You'll Learn- Develop using deep learning algorithms- Build deep learning models using TensorFlow 2- Create classification systems and other, practical deep learning applicationsWho This Book Is ForStudents, programmers, and researchers with no experience in deep learning who want to build up their basic skillsets. Experienced machine learning programmers and engineers might also find value in updating their skills | ||
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| institution | BVB |
| isbn | 9781484279144 |
| language | English |
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| owner_facet | DE-29T |
| physical | xxiii, 713 Seiten Illustrationen, Diagramme 1116 grams |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Apress |
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| spelling | Zeng, Xiangming aut Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks Liangqu Long, Xiangming Zeng 1st ed Berkeley, CA Apress [2022] xxiii, 713 Seiten Illustrationen, Diagramme 1116 grams txt rdacontent n rdamedia nc rdacarrier Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! What You'll Learn- Develop using deep learning algorithms- Build deep learning models using TensorFlow 2- Create classification systems and other, practical deep learning applicationsWho This Book Is ForStudents, programmers, and researchers with no experience in deep learning who want to build up their basic skillsets. Experienced machine learning programmers and engineers might also find value in updating their skills Machine learning Hardcover, Softcover / Informatik, EDV/Informatik Long, Liangqu aut Erscheint auch als Online-Ausgabe 978-1-4842-7915-1 |
| spellingShingle | Zeng, Xiangming Long, Liangqu Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks Machine learning |
| title | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks |
| title_auth | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks |
| title_exact_search | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks |
| title_exact_search_txtP | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks |
| title_full | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks Liangqu Long, Xiangming Zeng |
| title_fullStr | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks Liangqu Long, Xiangming Zeng |
| title_full_unstemmed | Beginning Deep Learning with TensorFlow work with Keras, MNIST Data Sets, and Advanced Neural Networks Liangqu Long, Xiangming Zeng |
| title_short | Beginning Deep Learning with TensorFlow |
| title_sort | beginning deep learning with tensorflow work with keras mnist data sets and advanced neural networks |
| title_sub | work with Keras, MNIST Data Sets, and Advanced Neural Networks |
| topic | Machine learning |
| topic_facet | Machine learning |
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