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Python reinforcement learning projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow by
  • Saito, Sean
  • Wenzhuo, Yang
  • Shanmugamani, Rajalingappaa
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Publication details: Mumbai: Packt, ©2019
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TensorFlow machine learning projects: Build 13 real-world projects with advanced numerical computations using the Python ecosystem by
  • Jain, Ankit
  • Fandango, Armando
  • Kapoor, Amita
Material type: Text Text; Format: print ; Literary form: Not fiction
Publication details: Mumbai: Packt, ©2018
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Deep learning with PyTorch: A practical approach to building neural network models using Pytorch by
  • Subramanian, Vishnu
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Publication details: Mumbai: Packt, ©2017
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Hands-on serverless deep learning with Tensorflow and AWS lambda: Training serverless deep learning models using the AWS infrastructure by
  • Feyzkhanov, Rustem
Edition: 1st
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Publication details: Mumbai: Packt, ©2019
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Deep learning with Theano: Perform large-scale numerical and scientific computations efficiently by
  • Bourez, Christopher
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Publication details: Mumbai: Packt, ©2017
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Python artificial intelligence projects for beginners: Get up and running with artificial intelligence using 8 smart and exciting AI applications by
  • Eckroth, Joshua
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Publication details: Mumbai: Packt, ©2018
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Machine learning for healthcare analytics projects: Build smart AI applications using neural network methodologies across the healthcare vertical market by
  • Eduonix Learning Solutions
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Publication details: Mumbai: Packt, ©2018
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Hands-on data analysis with NumPy and pandas: Implement Python packages from data manipulation to processing by
  • Miller, Curtis
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Publication details: Mumbai: Packt, ©2018
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Hands-on data science with the command line: Automate everyday data science tasks using command-line tools by
  • Morris, Jason
  • McCubbin, Chris
  • Page, Raymond
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Deep learning quick reference: Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras by
  • Bernico, Mike
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Deep learning with hadoop: Build, implement and scale distributed deep learning models for large-scale datasets by
  • Dev, Dipayan
Edition: 1st
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Advanced deep learning with keras: Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients. by
  • Atienza, Rowel
Edition: 1st ed.
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Android development with Kotlin: Enhance your skills for android development using Kotlin by
  • Moskala, Marcin
  • Wojda, Igor
Edition: 1st
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Architecting modern Java EE applications: Designing lightweight, business-oriented enterprise applications in the age of cloud, containers and Java EE 8 by
  • Blevins, David
Edition: 1st
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Artificial intelligence by example: Develop machine intelligence from scratch using real artificial intelligence use cases by
  • Rothman, Denis
Edition: 1st
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Artificial intelligence with Python: Build real-world artificial intelligence applications with python to intelligent interact with the world around you by
  • Joshi, Prateek
Edition: 1st
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Big data analytics with R: Leverage R programming to uncover hidden patterns in your big data by
  • Walkowiak, Simon
Edition: 1st
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Publication details: Mumbai: Packt, ©2016
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Cloud analytics with google cloud platform by
  • Thodge, Sanket
Edition: 1st
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Cloud native architectures: Design high-availability and cost-effective applications for the cloud by
  • Laszewski, Tom
Edition: 1st
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Data analysis with Python: A modern approach by
  • Taieb, David
Edition: 1st
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