Buch, Englisch, 366 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 1000 g
Buch, Englisch, 366 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 1000 g
ISBN: 978-0-323-90198-7
Verlag: William Andrew Publishing
Deep Learning has been successfully applied in diverse fields such as computer vision, audio processing, robotics, natural language processing, bioinformatics and chemistry. Because of the huge scope of knowledge in Deep Learning, a lot of time is required to understand and deploy useful, working applications, hence the importance of this new resource. Both theory lessons and experiments are included in each chapter to introduce the techniques and provide source code examples to practice using them. All Labs for this book are placed on GitHub to facilitate the download. The book is written based on the assumption that the reader knows basic Python for programming and basic Machine Learning.
Autoren/Hrsg.
Fachgebiete
- Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie Lernen
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein E-Learning
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
Weitere Infos & Material
1. Introduction to TensorFlow2.02. Regression Problem3. Binary classification problem4. Multi-category Classification Problem5. Training Neural Network6. Advanced TensorFlow2.07. Advanced TensorBoard8. Convolutional Neural Network Architectures9. Transfer Learning10. Variational Auto-Encoder11. WGAN-GP12. Object Detection