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Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition
Data Science Algorithms in a Week: Top 7 algorithms for scientific computing, data analysis, and machine learning, 2nd Edition

Build a strong foundation of machine learning algorithms in 7 days

Key Features

  • Use Python and its wide array of machine learning libraries to build predictive models
  • Learn the basics of the 7 most widely used machine learning algorithms within a week
  • Know...
Hands-On Software Engineering with Python: Move beyond basic programming and construct reliable and efficient software with complex code
Hands-On Software Engineering with Python: Move beyond basic programming and construct reliable and efficient software with complex code

Explore various verticals in software engineering through high-end systems using Python

Key Features

  • Master the tools and techniques used in software engineering
  • Evaluates available database options and selects one for the final Central Office system-components
  • ...
Beginning DevOps with Docker: Automate the deployment of your environment with the power of the Docker toolchain
Beginning DevOps with Docker: Automate the deployment of your environment with the power of the Docker toolchain
It can be tough to roll out a pre-configured environment if you don't know what you're doing. We'll show you how to streamline your service options with Docker, so that you can scale in an agile and responsive manner.
Key Features
  • Learn how to structure your own Docker containers
  • ...
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras
Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem

Key Features

  • Build deep learning models with transfer learning principles in Python
  • implement transfer learning to solve real-world research...
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

  • Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow
  • Explore deep neural...
CCSP (ISC)2 Certified Cloud Security Professional Official Study Guide
CCSP (ISC)2 Certified Cloud Security Professional Official Study Guide

The only official study guide for the new CCSP exam

CCSP (ISC)2 Certified Cloud Security Professional Official Study Guide is your ultimate resource for the CCSP exam. As the only official study guide reviewed and endorsed by (ISC)2, this guide helps you prepare faster and smarter...

Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence
Hands-On Computer Vision with Julia: Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking.

Key Features

  • Build a full-fledged image processing application using JuliaImages
  • Perform basic to advanced image and video stream...
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks

Key Features

  • Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision
  • Combine the power of Python, Keras, and TensorFlow to...
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow

A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python

Key Features

  • Enter the world of artificial intelligence using the power of Python
  • An example-rich guide to master various RL and DRL algorithms
  • Explore...
Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras
Natural Language Processing and Computational Linguistics: A practical guide to text analysis with Python, Gensim, spaCy, and Keras

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms.

Key Features

  • Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and...
Practical Mobile Forensics - Third Edition: A hands-on guide to mastering mobile forensics for the iOS, Android, and the Windows Phone platforms
Practical Mobile Forensics - Third Edition: A hands-on guide to mastering mobile forensics for the iOS, Android, and the Windows Phone platforms

Investigate, analyze, and report iOS, Android, and Windows devices

Key Features

  • Get hands-on experience in performing simple to complex mobile forensics techniques
  • Retrieve and analyze data stored not only on mobile devices but also through the cloud and other connected...
An Introduction to 3D Computer Vision Techniques and Algorithms
An Introduction to 3D Computer Vision Techniques and Algorithms

Computer vision encompasses the construction of integrated vision systems and the application of vision to problems of real-world importance. The process of creating 3D models is still rather difficult, requiring mechanical measurement of the camera positions or manual alignment of partial 3D views of a scene. However using algorithms, it is...

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