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Learn Python Programming: The no-nonsense, beginner's guide to programming, data science, and web development with Python 3.7, 2nd Edition
Learn Python Programming: The no-nonsense, beginner's guide to programming, data science, and web development with Python 3.7, 2nd Edition

Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects.

Key Features

  • Learn the fundamentals of Python programming with interactive projects
  • Apply Python to data...
Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library
Natural Language Processing with TensorFlow: Teach language to machines using Python's deep learning library

Write modern natural language processing applications using deep learning algorithms and TensorFlow

Key Features

  • Focuses on more efficient natural language processing using TensorFlow
  • Covers NLP as a field in its own right to improve understanding for choosing TensorFlow...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Post-Silicon Validation and Debug
Post-Silicon Validation and Debug

This book provides a comprehensive coverage of System-on-Chip (SoC) post-silicon validation and debug challenges and state-of-the-art solutions with contributions from SoC designers, academic researchers as well as SoC verification experts.  The readers will get a clear understanding of the existing debug infrastructure and how...

Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi
Intelligent Mobile Projects with TensorFlow: Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow

Key Features

  • Build TensorFlow-powered AI applications for mobile and embedded devices
  • Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning
  • ...
R Deep Learning Projects: Master the techniques to design and develop neural network models in R
R Deep Learning Projects: Master the techniques to design and develop neural network models in R

5 real-world projects to help you master deep learning concepts

Key Features

  • Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more
  • Get to grips with R's impressive range of...
Computer Forensics: Computer Crime Scene Investigation (With CD-ROM) (Networking Series)
Computer Forensics: Computer Crime Scene Investigation (With CD-ROM) (Networking Series)
The mightiest fortresses in the world can fail, and when that happens all you can do (you being the person responsible for castle security) is figure out what went wrong, what damage was done, and by whom. If the castle was located in the right kind of kingdom--to take a metaphor too far--you can hope to prosecute the perpetrator. Computer...
Introduction to the Theory of Computation
Introduction to the Theory of Computation

You are about to embark on the study of a fascinating and important subject: the theory of computation. It comprises the fundamental mathematical properties of computer hardware, software, and certain applications thereof. In studying this subject we seek to determine what can and cannot be computed, how quickly, with how much memory,...

R Deep Learning Essentials
R Deep Learning Essentials

Key Features

  • Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
  • Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
  • Build models relating to neural...
Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server
Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server
Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.

It is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or
...
Hands-On System Programming with Go: Build modern and concurrent applications for Unix and Linux systems using Golang
Hands-On System Programming with Go: Build modern and concurrent applications for Unix and Linux systems using Golang

Explore the fundamentals of systems programming starting from kernel API and filesystem to network programming and process communications

Key Features

  • Learn how to write Unix and Linux system code in Golang v1.12
  • Perform inter-process communication using pipes, message...
Augmented Reality using Appcelerator Titanium Starter
Augmented Reality using Appcelerator Titanium Starter
I first starting thinking about human/machine augmentations in 2000 when I started a company focused in the Telco software space. Initially, I focused on how to enable wireless content development, but at that time, devices were primitive. High speed networks hadn't fully taken on in many areas of the U.S. for mobile networks...
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