- Go Cashless: Get 10% cashback up to Rs. 50 using BHIM UPI or RuPay cards. Offer period October 1st to October 31st. Cashback will be credited as Amazon Pay balance within 15 calendar days from purchase. Here's how (terms and conditions apply)
- Go Cashless: Get 50% cashback up to Rs. 100 on your first online payment. Pay using ATM card or credit card. Offer period 1st October to 31st October. Cashback will be credited as Amazon Pay balance within 15 days from purchase. Here's how (terms and conditions apply)
Other Sellers on Amazon
+ 150.00 Delivery charge
+ 200.00 Delivery charge
Deep Learning with TensorFlow Paperback – Import, 24 Apr 2017
Special offers and product promotions
Frequently bought together
Customers who bought this item also bought
About the Author
Giancarlo Zaccone has more than ten years of experience in managing research projects both in scientific and industrial areas. He worked as researcher at the C.N.R, the National Research Council, where he was involved in projects relating to parallel computing and scientific visualization. Currently, he is a system and software engineer at a consulting company developing and maintaining software systems for space and defense applications. He is author of the following Packt volumes: Python Parallel Programming Cookbook and Getting Started with TensorFlow. Md. Rezaul Karim has more than 8 years of experience in the area of research and development with a solid knowledge of algorithms and data structures, focusing C/C++, Java, Scala, R, and Python and big data technologies such as Spark, Kafka, DC/OS, Docker, Mesos, Hadoop, and MapReduce. His research interests include machine learning, deep learning, Semantic Web, big data, and bioinformatics. He is the author of the book titled Large-Scale Machine Learning with Spark, Packt Publishing. He is a Software Engineer and Researcher currently working at the Insight Center for Data Analytics, Ireland. He is also a Ph.D. candidate at the National University of Ireland, Galway. He also holds a BS and an MS degree in Computer Engineering. Before joining the Insight Centre for Data Analytics, he had been working as a Lead Software Engineer with Samsung Electronics, where he worked with the distributed Samsung R&D centers across the world, including Korea, India, Vietnam, Turkey, and Bangladesh. Before that, he worked as a Research Assistant in the Database Lab at Kyung Hee University, Korea. He also worked as an R&D Engineer with BMTech21 Worldwide, Korea. Even before that, he worked as a Software Engineer with i2SoftTechnology, Dhaka, Bangladesh. 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 Machine Learning and Natural Language Processing (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 Machine Learning, Image Processing, Linear Algebra, Probability and Statistics, Data structures, Essential Mathematics for Computer Science. Next, he joined as a research scientist at the Industrial research and development lab at IST Networks, based in Egypt. He was involved in implementing the state-of-the-art system for Arabic Text to Speech. Consequently, he was the main machine learning specialist in that company. Later on, he joined the Insight Centre for Data Analytics, the National University of Ireland at Galway as a Research Assistant working on building a Predictive Analytics Platform. Finally, he joined ADAPT Centre, Trinity College Dublin as a Research Engineer. His main role in ADAPT is to build prototypes and applications using ML and NLP techniques based on the research that is done within ADAPT.
Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required.
To get the free app, enter mobile phone number.
Customers who viewed this item also viewed
Most helpful customer reviews on Amazon.com
"Machine Learning with TensorFlow" by Shukla, published by Manning in 2018-02, 272 pp, $43
"Mastering TensorFlow 1.x" by Fandango, Packt, 2018-01, 474 pp, $35
"Pro Deep Learning with TensorFlow" by Pattanayak, Apress, 2017-12, 398 pp, $37
"TensorFlow 1.x Deep Learning Cookbook" by Gulli and Kapoor, Packt, 2017-12, 536 pp, $32
"Neural Network Programming with TensorFlow" by Ghotra and Dua, Packt, 2017-11, 274 pp, $40
"Predictive Analytics with TensorFlow" by Karim, Packt, 2017-11, 522 pp, $50
"Machine Learning with TensorFlow 1.x" by Hua and Azeem, Packt, 2017-11, 304 pp, $39
"Learning TensorFlow" by Hope and Resheff, O'Reilly, 2017-08, 242 pp, $25
"Hands-On Deep Learning with TensorFlow" by Van Boxel, Packt, 2017-07, 174 pp, $35
"Deep Learning with TensorFlow" by Zaccone, Karim, Menshawy, Packt, 2017-04, 320 pp, $50
"TensorFlow Machine Learning Cookbook" by McClure, Packt, 2017-02, 370 pp, $30
"Building Machine Learning Projects with TensorFlow" by Bonnin, Packt, 2016-11, 291 pp, $35
"Getting Started with TensorFlow" by Zaccone, Packt, 2016-07, 180 pp, $35
I reviewed the doc on tensorflow.org - including the doc for older releases - then started looking at books. One week later, I am still not done, but have winnowed out some options. The books by Van Boxel and Zaccone are out - these are brief (and not up-to-date) introductions, costing as much as more substantial titles - and the book by Karim is "disqualified" for blatant plagiarism.
What happens when Messrs Zaccone and Karim collaborate? It seems that the former continues to do honest work, and the latter continues to pilfer content. I am reading an electronic copy and cannot point to page numbers, but a chunk of "Neural networks as computational graphs" Section in Chapter 1 seems to be purloined from Brandon Brown of Outlace.com (see post "On chain rule, computational graphs, and back-propagation"), and Chapter 10, "Reinforcement learning", is taken without attribution from Arthur Juliani. Sorry, I have to stop here, give one star and move on. It's a pity, because "Deep Learning with TensorFlow" has substance - as copy-pastes go, this is a fairly wide-ranging, and undeniably enriched, copy-paste - but plagiarism should not be encouraged.
I'm in Ch 3 and scrapping the book for something else. Sad.
I have seen improvements in Ch4 with CNN's the code is cleaner and the explanation is improving.