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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...
Linux Administration Cookbook: Insightful recipes to work with system administration tasks on Linux
Linux Administration Cookbook: Insightful recipes to work with system administration tasks on Linux

Over 100 recipes to get up and running with the modern Linux administration ecosystem

Key Features

  • Understand and implement the core system administration tasks in Linux
  • Discover tools and techniques to troubleshoot your Linux system
  • Maintain a healthy...
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances

Create AI applications in Python and lay the foundations for your career in data science

Key Features

  • Practical examples that explain key machine learning algorithms
  • Explore neural networks in detail with interesting examples
  • Master core AI concepts with...
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python
Hands-On Machine Learning for Algorithmic Trading: Design and implement investment strategies based on smart algorithms that learn from data using Python

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras

Key Features

  • Implement machine learning algorithms to build, train, and validate algorithmic models
  • Create your own algorithmic design process to apply...
Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques
Artificial Intelligence for Robotics: Build intelligent robots that perform human tasks using AI techniques

Bring a new degree of interconnectivity to your world by building your own intelligent robots

Key Features

  • Leverage fundamentals of AI and robotics
  • Work through use cases to implement various machine learning algorithms
  • Explore Natural Language Processing...
Python Robotics Projects: Build smart and collaborative robots using Python
Python Robotics Projects: Build smart and collaborative robots using Python

Leverage the power of Python to build DIY robotic projects

Key Features

  • Design, build, and stimulate collaborative robots
  • Build high-end robotics projects such as a customized personal Jarvis
  • Leverage the power of Python and ROS for DIY robotic...
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer.

Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware...
Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition
Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology, 2nd Edition

Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data

Key Features

  • Perform complex bioinformatics analysis using the most important Python libraries and applications
  • Implement next-generation sequencing,...
Building Intelligent Systems: A Guide to Machine Learning Engineering
Building Intelligent Systems: A Guide to Machine Learning Engineering
Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success.


This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your
...
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Build, scale, and deploy deep neural network models using the star libraries in Python

Key Features

  • Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras
  • Build, deploy, and scale end-to-end deep neural network models in a production...
Advanced Deep Learning with Keras: Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more
Advanced Deep Learning with Keras: Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more

A comprehensive guide to advanced deep learning techniques, including autoencoders, GANs, VAEs, and deep reinforcement learning that drive today's most impressive AI results

Key Features

  • Explore the most advanced deep learning techniques that drive modern AI results
  • ...
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

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