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Deep Learning with TensorFlow. Explore neural networks with Python Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy

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Deep Learning with TensorFlow. Explore neural networks with Python Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy - okladka książki

Deep Learning with TensorFlow. Explore neural networks with Python Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy - okladka książki

Deep Learning with TensorFlow. Explore neural networks with Python Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy - audiobook MP3

Deep Learning with TensorFlow. Explore neural networks with Python Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy - audiobook CD

Autorzy:
Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
320
Dostępne formaty:
     PDF
     ePub
     Mobi
Deep learning is the step that comes after machine learning, and has more advanced
implementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x.

Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including
search, image recognition, and language processing. Additionally, you’ll learn how
to analyze and improve the performance of deep learning models. This can be done by
comparing algorithms against benchmarks, along with machine intelligence, to learn
from the information and determine ideal behaviors within a specific context.

After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects.

Wybrane bestsellery

O autorach książki

Giancarlo Zaccone has over fifteen years' experience of managing research projects in the scientific and industrial domains. He is a software and systems engineer at the European Space Agency (ESTEC), where he mainly deals with the cybersecurity of satellite navigation systems.



Giancarlo holds a master's degree in physics and an advanced master's degree in scientific computing.



Giancarlo has already authored the following titles, available from Packt: Python Parallel Programming Cookbook (First Edition), Getting Started with TensorFlow, Deep Learning with TensorFlow (First Edition), and Deep Learning with TensorFlow (Second Edition).
Md. Rezaul Karim is a researcher, author, and data science enthusiast with a strong computer science background, coupled with 10 years of research and development experience in machine learning, deep learning, and data mining algorithms to solve emerging bioinformatics research problems by making them explainable. He is passionate about applied machine learning, knowledge graphs, and explainable artificial intelligence (XAI).
Currently, he is working as a research scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he worked as a researcher at the Insight Centre for Data Analytics, Ireland. Previously, he worked as a lead software engineer at Samsung Electronics, Korea.
Ahmed Menshawy is a Research Engineer at the Trinity College Dublin, Ireland. He has more than 5 years of working experience in the area of ML and NLP. He holds an MSc in Advanced Computer Science. He started his Career as a Teaching Assistant at the Department of Computer Science, Helwan University, Cairo, Egypt. He taught several advanced ML and NLP courses such as ML, Image Processing, and so on. He was involved in implementing the state-of-the-art system for Arabic Text to Speech. He was the main ML specialist at the Industrial research and development lab at IST Networks, based in Egypt.

Giancarlo Zaccone, Md. Rezaul Karim, Ahmed Menshawy - pozostałe książki

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