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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind;

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Medical Image Computing and Computer Assisted Intervention - MICCAI 2021

learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning;

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Event Attendance Prediction in Social Networks

book illustrates how these attributes can be applied for event attendance prediction by incorporating them into supervised learning models, and;

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Machine Learning and Data Science Blueprints for Finance From Building Trading Strategies to RoboAdvisors Using Python

over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for;

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TensorFlow 2.0 Quick Start Guide

your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced;

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Machine Learning Foundations

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning;

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Wind Forecasting in Railway Engineering

and reinforcement learning methodsCombines the latest thinking from wind engineering and railway engineeringOffers a;

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Mastering Machine Learning Algorithms

data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement;

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Machine Learning in Radiation Oncology

, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised;

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Forecasting and Assessing Risk of Individual Electricity Peaks

The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction;

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Machine Learning for Knowledge Discovery with R

Machine Learning for Knowledge Discovery with R contains methodologies and examples for statistical modelling, inference, and prediction;

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Advanced Forecasting with Python

supervised learning, to state-of-the-art deep forecasting models such as LSTMs, recurrent neural networks, Facebooks open-source Prophet model, and;

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Applied Supervised Learning with R

detection in driver less cars, customer churn, and loan default prediction. Key Features Study supervised learning algorithms by using real-world;

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Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This;

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Machine Learning Methods in the Environmental Sciences

Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This;

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Prediction, Learning, and Games

This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a;

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Applied Genetic Programming and Machine Learning

What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks;

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Applied Genetic Programming and Machine Learning

What do financial data prediction, day-trading rule development, and bio-marker selection have in common? They are just a few of the tasks;

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Machine Learning for Time Series Forecasting with Python

machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and;

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Machine Learning with scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering;

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Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track

: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised;

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Machine Learning and Knowledge Discovery in Databases. Research Track

: Part I: Online learning; reinforcement learning; time series, streams, and sequence models; transfer and multi-task learning; semi-supervised;

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Supervised Machine Learning with Python

Teach your machine to think for itself! Key Features Delve into supervised learning and grasp how a machine learns from data Implement;

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Applied Supervised Learning with Python

Understand the concept of supervised learning and its applications Implement common supervised learning algorithms using machine learning Python;

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Machine Learning for Protein Subcellular Localization Prediction

Comprehensively covers protein subcellular localization from single-label prediction to multi-label prediction, and includes prediction;

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Applied Machine Learning for Smart Data Analysis

unsupervised and semi-supervised machine learning techniques with study of semantic analysis and thorough analysis of reviews. Divided into sections;

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Digitization in Controlling

in the working capital. The author manages to prove that both a trained forecasting algorithm achieves a prediction accuracy of 92.49 % and;

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Einde inhoud

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