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Algorithms
Algorithms
This book is intended to survey the most important algorithms in use on
computers today and to teach fundamental techniques to the growing number
of people who are interested in becoming serious computer users. It is appropriate
for use as a textbook for a second, third or fourth course in computer
science: after students have
...
Visual Perception for Humanoid Robots: Environmental Recognition and Localization, from Sensor Signals to Reliable 6D Poses (Cognitive Systems Monographs (38))
Visual Perception for Humanoid Robots: Environmental Recognition and Localization, from Sensor Signals to Reliable 6D Poses (Cognitive Systems Monographs (38))
This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental...
Deep Learning with PyTorch: A practical approach to building neural network models using PyTorch
Deep Learning with PyTorch: A practical approach to building neural network models using PyTorch

Build neural network models in text, vision and advanced analytics using PyTorch

Key Features

  • Learn PyTorch for implementing cutting-edge deep learning algorithms.
  • Train your neural networks for higher speed and flexibility and learn how to implement them in various...
Algorithms in Java: Parts 1-4, Third Edition
Algorithms in Java: Parts 1-4, Third Edition

Sedgewick has a real gift for explaining concepts in a way that makes them easy to understand. The use of real programs in page-size (or less) chunks that can be easily understood is a real plus. The figures, programs, and tables are a significant contribution to the learning experience of the reader; they make this book...

Python Reinforcement Learning Projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
Python Reinforcement Learning Projects: Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow

Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries

Key Features

  • Implement Q-learning and Markov models with Python and OpenAI
  • Explore the power of TensorFlow to build self-learning models
  • Eight AI...
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...
Learn Java 12 Programming: A step-by-step guide to learning essential concepts in Java SE 10, 11, and 12
Learn Java 12 Programming: A step-by-step guide to learning essential concepts in Java SE 10, 11, and 12

A comprehensive guide to get started with Java and gain insights into major concepts such as object-oriented, functional, and reactive programming

Key Features

  • Strengthen your knowledge of important programming concepts and the latest features in Java
  • Explore core...
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...
Algorithms and Programming: Problems and Solutions (Modern Birkhäuser Classics)
Algorithms and Programming: Problems and Solutions (Modern Birkhäuser Classics)
Somebody once said that one may prove the correctness of an algorithm, but not of a program. One of the main goals of this book is to convince the reader that things are not so bad.

A well-known programmer, C.A.R. Hoare, said that the beauty of a program is not an additional benefit but a criterion that separates success from failure.
...
Deep Learning: Convergence to Big Data Analytics (SpringerBriefs in Computer Science)
Deep Learning: Convergence to Big Data Analytics (SpringerBriefs in Computer Science)

This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques...

Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along...
Linear and Nonlinear Programming: Third Edition (International Series in Operations Research & Management Science)
Linear and Nonlinear Programming: Third Edition (International Series in Operations Research & Management Science)
"Linear and Nonlinear Programming" is considered a classic textbook in Optimization. While it is a classic, it also reflects modern theoretical insights. These insights provide structure to what might otherwise be simply a collection of techniques and results, and this is valuable both as a means for learning existing material and for...
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