Learn IT - Books tags models

Digitalization Cases: How Organizations Rethink Their Business for the Digital Age (Management for Professionals)

Springer, 2018

This book presents a rich compilation of real-world cases on digitalization, the goal being to share first-hand insights from respected organizations and to make digitalization more tangible. As virtually every economic and societal sector is now being challenged by emerging technologies, the digital economy is a highly...

Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Packt Publishing, 2019

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...

Satellite Image Analysis: Clustering and Classification (SpringerBriefs in Applied Sciences and Technology)

Springer, 2019

Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision...

Practical Modelling of Dynamic Decision Making (SpringerBriefs in Intelligent Systems)

Springer, 2019

This book presents TDF (Tactics Development Framework), a practical methodology for eliciting and engineering models of expert decision-making in dynamic domains. The authors apply the BDI (Beliefs, Desires, Intentions) paradigm to the elicitation and modelling of dynamic decision making expertise, including team behaviour, and map...

Discrete Element Method in the Design of Transport Systems: Verification and Validation of 3D Models

Springer, 2019

This book deals with the design and optimization of the bucket elevator using the discrete element method (DEM). It describes the underlying scientific basis for the design of transport equipment using computer simulations and is focused on issues relevant to the industrial sector, mechanical engineering; and the transport, treatment,...

Learn TensorFlow 2.0: Implement Machine Learning and Deep Learning Models with Python

Apress, 2020

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples.

The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0....

Django RESTful Web Services: The easiest way to build Python RESTful APIs and web services with Django

Packt Publishing, 2018

Design, build and test RESTful web services with the Django framework and Python

Key Features

Create efficient real-world RESTful web services with the latest Django framework

Authenticate, secure, and integrate third-party packages efficiently in your Web Services

...

Handbook of Approximate Bayesian Computation (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

CRC Press, 2018

As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but...

Data Model Patterns: A Metadata Map (The Morgan Kaufmann Series in Data Management Systems)

Morgan Kaufmann, 2006

A very ambitious undertaking, masterfully described. To the best of my knowledge, this is the first published version of the detailed models implied by the Zachman Framework. David Hay builds the models one step at a time, describing in each increment why the new entities were added, and how they related to the rest of the model. At least as...

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

Packt Publishing, 2018

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...

Beginning Django: Web Application Development and Deployment with Python

Apress, 2017

Discover the Django web application framework and get started building Python-based web applications. This book takes you from the basics of Django all the way through to cutting-edge topics such as creating RESTful applications. Beginning Django also covers ancillary, but essential, development topics, including...

Arduino Programming with .NET and Sketch

Apress, 2017

Leverage .NET and Sketch in your Arduino development implementation and integrate it into your .NET program.

There are many Arduino models and compatible shields that can be used in Arduino boards. Integrating between an Arduino platform and .NET technology or Sketch can produce more...

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