Massive Free Documents

Discover millions of professional documents covering academic, business, culture and more.

Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

Secure and Privacy-Preserving Automated Machine Learning Operations into End-to-End Integrated IoT-Edge-Artificial Intelligence-Blockchain Monitoring System for Diabetes Mellitus Prediction

Artificial Intelligence for the Prediction of Weaning Readiness Outcome in a Multi-centrical Clinical Cohort of Mechanically Ventilated Patients - Tesi di Laurea

Artificial Intelligence for the Prediction of Weaning Readiness Outcome in a Multi-centrical Clinical Cohort of Mechanically Ventilated Patients - Tesi di Laurea

Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α‑Synuclein Secondary Nucleation

Exploration and Exploitation Approaches Based on Generative Machine Learning to Identify Potent Small Molecule Inhibitors of α‑Synuclein Secondary Nucleation

Multitemporal Analysis in Google Earth Engine - Detecting Urban Changes Using Optical Data and Machine Learning Algorithms

Multitemporal Analysis in Google Earth Engine - Detecting Urban Changes Using Optical Data and Machine Learning Algorithms

Machine learning based analysis for intellectual disability in Down syndrome

Machine learning based analysis for intellectual disability in Down syndrome

EWSmethods - an R package to forecast tipping points at the community level using early warning signals, resilience measures, and machine learning models

EWSmethods - an R package to forecast tipping points at the community level using early warning signals, resilience measures, and machine learning models

Computational Notebooks as Co-Design Tools - Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning Models

Computational Notebooks as Co-Design Tools - Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning Models

Assessing accuracy of machine learning-based protein structure prediction model with molecular dynamics stabilization simulations - Master’s thesis

Assessing accuracy of machine learning-based protein structure prediction model with molecular dynamics stabilization simulations - Master’s thesis

From Isotopes and Whole Rock Geochemistry to Machine Learning - Diving into the Plumbing System of Large Mafic Eruptions Using a Diverse Geochemical Toolset to Investigate Magmatic Processes

From Isotopes and Whole Rock Geochemistry to Machine Learning - Diving into the Plumbing System of Large Mafic Eruptions Using a Diverse Geochemical Toolset to Investigate Magmatic Processes

Sports Analytics - Performance Prediction - Master of Science (MSc) in Data Science Thesis

Sports Analytics - Performance Prediction - Master of Science (MSc) in Data Science Thesis

Optimisation for Efficient Deep Learning - Doctor of Philosophy thesis

Optimisation for Efficient Deep Learning - Doctor of Philosophy thesis

Comparison of Machine Learning and Statistical Methods in the Field of Renewable Energy Power Generation Forecasting - Mini Review

Comparison of Machine Learning and Statistical Methods in the Field of Renewable Energy Power Generation Forecasting - Mini Review

Detection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning

Detection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning

Assessing Uncertainty and Heterogeneity in Machine Learning-Based Spatiotemporal Ozone Prediction in the Beijing-Tianjin-Hebei Region in China

Assessing Uncertainty and Heterogeneity in Machine Learning-Based Spatiotemporal Ozone Prediction in the Beijing-Tianjin-Hebei Region in China

Using the Interest Theory of Rights and Hohfeldian Taxonomy to Address a Gap in Machine Learning Methods for Legal Document Analysis

Using the Interest Theory of Rights and Hohfeldian Taxonomy to Address a Gap in Machine Learning Methods for Legal Document Analysis