Sarkar / Panwar / Bali Hands-On Transfer Learning with Python

Implement advanced deep learning and neural network models using TensorFlow and Keras
1. Auflage 2018
ISBN: 978-1-78883-905-1
Verlag: De Gruyter
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 438 Seiten

No detailed description available for "Hands-On Transfer Learning with Python".

Autoren/Hrsg.

Sarkar, Dipanjan

Panwar, Nitin

Bali, Raghav

Ghosh, Tamoghna

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

Table of Contents - Machine Learning Fundamentals
- Deep Learning Essentials
- Understanding Deep Learning Architectures
- Transfer Learning Fundamentals
- Unleash the Power of Transfer Learning
- Image Recognition and Classification
- Text Document Categorization
- Audio Identification and Categorization
- Deep Dream
- Neural Style Transfer
- Automated Image Caption Generator
- Image Colorization

Über Autor(innen)

Sarkar Dipanjan:
Dipanjan (DJ) Sarkar is a Data Scientist at Intel, leveraging data science, machine learning, and deep learning to build large-scale intelligent systems. He holds a master of technology degree with specializations in Data Science and Software Engineering. He has been an analytics practitioner for several years now, specializing in machine learning, NLP, statistical methods, and deep learning. He is passionate about education and also acts as a Data Science Mentor at various organizations like Springboard, helping people learn data science. He is also a key contributor and editor for Towards Data Science, a leading online journal on AI and Data Science. He has also authored several books on R, Python, machine learning, NLP, and deep learning.Ghosh Tamoghna:
Tamoghna Ghosh is a machine learning engineer at Intel Corporation. He has overall 11 years of work experience including 4 years of core research experience at Microsoft Research (MSR) India. At MSR he worked as a research assistant in cryptanalysis of block ciphers. His technical expertise's are in big data, machine learning, NLP, information retrieval, data visualization and software development. He received M.Tech (Computer Science) degree from the Indian Statistical Institute, Kolkata and M.Sc (Mathematics) from University of Calcutta with specialization in functional analysis and mathematical modeling/dynamical systems. He is passionate about teaching and conducts internal training in data science for Intel at various levels.