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Books tags: model
Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes
Machine Learning and AI for Healthcare: Big Data for Improved Health Outcomes

Explore the theory and practical applications of artificial intelligence (AI) and machine learning in healthcare. This book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare and big data challenges.

You’ll discover the...

Scaling Your Startup: Mastering the Four Stages from Idea to $10 Billion
Scaling Your Startup: Mastering the Four Stages from Idea to $10 Billion
Know how your company can accelerate growth by not only tapping into new growth vectors, but also by adapting its organization, culture, and processes.

To oversee growth from an idea to a company with billions in revenue, CEOs must reinvent many aspects of their company in anticipation of it reaching ever-higher revenues....
The IoT Hacker's Handbook: A Practical Guide to Hacking the Internet of Things
The IoT Hacker's Handbook: A Practical Guide to Hacking the Internet of Things
Take a practioner’s approach in analyzing the Internet of Things (IoT) devices and the security issues facing an IoT architecture.  

You’ll review the architecture's central components, from hardware communication interfaces, such as UARTand SPI, to radio protocols, such as BLE...
Artificial Neural Networks with Java: Tools for Building Neural Network Applications
Artificial Neural Networks with Java: Tools for Building Neural Network Applications
Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural...
Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
Hidden Markov Models for Time Series: An Introduction Using R (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Reveals How HMMs Can Be Used as General-Purpose Time Series Models

Implements all methods in R
Hidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and...

Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
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...
Concepts of Database Management
Concepts of Database Management
This concise yet comprehensive introduction to fundamental database concepts is an indispensable resource to develop your knowledge of database management concepts. Now in its sixth edition, Concepts of Database Management maintains the focus on real-world cases that made previous editions so effective addressing the most current database issues...
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Simulation-Based Algorithms for Markov Decision Processes (Communications and Control Engineering)
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences.  Many real-world problems modeled by MDPs have huge state and/or action spaces, giving an opening to the curse of dimensionality and so making practical...
Practical Guide to MIMO Radio Channel: with MATLAB Examples
Practical Guide to MIMO Radio Channel: with MATLAB Examples
This book provides an excellent reference to the MIMO radio channel

In this book, the authors introduce the concept of the Multiple Input Multiple Output (MIMO) radio channel, which is an intelligent communication method based upon using multiple antennas. Moreover, the authors provide a summary of the current channel...

The Art of Modeling in Science and Engineering with Mathematica
The Art of Modeling in Science and Engineering with Mathematica
Modeling is practiced in engineering and all physical sciences. Many specialized texts exist - written at a high level - that cover this subject. However, students and even professionals often experience difficulties in setting up and solving even the simplest of models. This can be attributed to three difficulties: the proper choice of model,...
Probabilistic Databases (Synthesis Lectures on Data Management)
Probabilistic Databases (Synthesis Lectures on Data Management)
Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of...
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