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Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

OPENALEX

Introduction to Machine Learning

Yalın Baştanlar, Mustafa Özuysal • Methods in molecular biology (2013)

The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity ...

OPENALEX Open Access DOI: https://doi.org/10.1007/978-1-62703-748-8_7

Machine learning in bioinformatics

Pedro Larrañaga, Borja Calvo, Roberto Santana, Concha Bielza et al. • Briefings in Bioinformatics (2006)

This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochast...

OPENALEX Open Access DOI: https://doi.org/10.1093/bib/bbk007

Machine Learning

Stephen Marsland • Chapman & Hall/CRC eBooks (2014)

A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing wo...

OPENALEX DOI: https://doi.org/10.1201/b17476

Optimization for Machine Learning

S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks (2011)

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...

OPENALEX DOI: https://doi.org/10.7551/mitpress/8996.001.0001

Introduction to Machine Learning

• Series in machine perception and artificial intelligence (2019)

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict ...

OPENALEX DOI: https://doi.org/10.1142/9789811201967_0001

Machine Learning

Ethem Alpaydın • The MIT Press eBooks (2021)

A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...

OPENALEX Open Access DOI: https://doi.org/10.7551/mitpress/13811.001.0001

Machine learning and deep learning

Christian Janiesch, Patrick Zschech, Kai Heinrich • Electronic Markets (2021)

Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of a...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12525-021-00475-2

Machine Learning

Peter A. Flach • Cambridge University Press eBooks (2012)

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511973000

Exploring the Impact of Alternatives of Object-Oriented Cohesion Measures on Machine Learning-Based Predictions of Inheritance Reusability

Jehad Al Dallal, Bader Alkhazi • IEEE Access (2024)

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3484007

Evaluation of the Applications of using Global free Digital Elevation Models and GNSS-RTK data for Agricultural purposes in Egypt using Machine Learning

Ashraf abdallah, Bara' Al-MISTAREHI, Amir SHTAYAT • JES: Journal of Engineering Sciences (2025)

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigat...

DOAJ Open Access (DOAJ) DOI: 10.21608/jesaun.2024.326709.1374

Global patterns of gully occurrence and their sensitivity to environmental changes

Yixian Chen, Sofie De Geeter, Jean Poesen, Francis Matthews et al. • International Soil and Water Conservation Research (2026)

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswcr.2025.09.004

LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles

Yong Wang, Hongwen He, Yuankai Wu, Pei Wang et al. • Engineering (2025)

An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasin...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.eng.2024.10.021