Machine Learning /

Machine Learning /

Bibliografiske detaljer
Hovedforfatter:	Mitchell, Tom M. (Tom Michael), 1951-
Format:	Bog
Sprog:	English
Udgivet:	New York : McGraw-Hill, c1997.
Udgivelse:	International edition.
Serier:	McGraw-Hill series in computer science
Fag:	Machine learning. Computer algorithms.
Classic Catalogue:	View this record in Classic Catalogue

Lignende værker

Foundations of machine learning /
af: Mohri, Mehryar, et al.
Udgivet: (2018)

Genetic algorithms in search, optimization, and machine learning /
af: Goldberg, David E. (David Edward), 1953-
Udgivet: (1989)

Smart biomedical device to predict lung diseases, COVID-19 and diabetes by using machine learning algorithms
af: Hossain, Ashraful, et al.
Udgivet: (2024)

Comparative analysis between machine learning algorithms in efficiency of Coronary Heart Disease (CHD) prediction
af: Oishi, Fayza Rezwana, et al.
Udgivet: (2020)

Understanding machine learning : from theory to algorithms /
af: Shalev-Shwartz, Shai
Udgivet: (2014)

Prediction of coronary heart diseases using supervised machine learning algorithms
af: Salam, Nazia Binte, et al.
Udgivet: (2023)

Subjectivity analysis using machine learning algorithm
af: Ahmed, Erfan, et al.
Udgivet: (2017)

Crowd source based traffic analysis using machine learning algorithm
af: Orthy, Marzia Khan, et al.
Udgivet: (2018)

Predicting criminal activities analyzing video signal using machine learning
af: Sadman, Syed Md., et al.
Udgivet: (2021)

Predictive maintenance of HVAC system using supervised machine learning algorithms
af: Fahim, Md. Zubayer Ahmed, et al.
Udgivet: (2021)

A machine learning approach on classifying orthopedic patients based on their biomechanical features
af: Hasan, Kamrul, et al.
Udgivet: (2018)

Approaching (almost) any Machine learning problem /
af: Thakur, Abhishek
Udgivet: (2020)

Prediction and detection in change of cognitive load for VIP’s by a machine learning approach
af: Rahman, Fahim, et al.
Udgivet: (2021)

Heart disease prediction using machine learning algorithms
af: Ali, Musfiq, et al.
Udgivet: (2019)

Pattern recognition and machine learning /
af: Bishop, Christopher M.
Udgivet: (2006)

Alumni opportunities using machine learning
af: Siaum, Arshif Sharlimin, et al.
Udgivet: (2019)

Analysing Facebook user risk using machine learning algorithm
af: Barua, Arnab, et al.
Udgivet: (2021)

Machine learning engineering /
af: Burkov, Andriy
Udgivet: (2020)

Public vehicle ETA system using machine learning
af: Kabir, Md. Miraz, et al.
Udgivet: (2018)

Study on human emotion based on facial expressions through human machine communication
af: Murshed, Tahmin Aysha, et al.
Udgivet: (2021)

Predicting depression in Bangladeshi undergraduates using machine learning
af: Choudhury, Ahnaf Atef, et al.
Udgivet: (2019)

Classi cation of magnetic configurations using machine learning algorithms
af: Bokul, Saffat, et al.
Udgivet: (2019)

Machine learning as an indicator for breast cancer prediction
af: Shadman, Tahsin Mohammed, et al.
Udgivet: (2019)

Crowed source based traffic analysis using machine learning algorithm
af: Orthy, Marzia Khan, et al.
Udgivet: (2017)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
af: Hossain, Shoumik, et al.
Udgivet: (2022)

The hundred-page machine learning /
af: Burkov, Andriy
Udgivet: (2019)

Predicting the length of stay in a hospital for a particular disease using machine learning algorithms
af: Imam, Saif
Udgivet: (2021)

Detecting online recruitment fraud by using machine learning
af: Ghosh, Gitanjali, et al.
Udgivet: (2021)

Analysis of the impact of online education using EEG signals and machine learning algorithms
af: Hoque, Ehsanul, et al.
Udgivet: (2021)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
af: Toufique, S.M, et al.
Udgivet: (2024)

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Predicting climate induced floods using machine learning
af: Saleh, Chowdhury Nafis, et al.
Udgivet: (2022)

The influence of neuromarketing: machine learning based empirical analysis
af: Muktadir, MD. Abdullah Al, et al.
Udgivet: (2024)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
af: Farabe, Abdullah Al, et al.
Udgivet: (2021)

Fault detection and predictive maintenance in IoT-based building management system using machine learning
af: Sabuj, Khaja Sheikh Imran, et al.
Udgivet: (2022)

Crop prediction based on geographical and climatic data using machine learning and deep learning
af: Alif, Al Amin, et al.
Udgivet: (2019)

Finding suitable locations for live campaigns using different machine learning techniques
af: Qudar, Mohiuddin Md. Abdul, et al.
Udgivet: (2018)

Phase Transitions in Machine Learning
af: Lorenza Saitta, Attilio Giordana, Antoine Cornuéjols
Udgivet: (2012)

Cardiovascular disease prediction model using Machine Learning Algorithm
af: Arefin Mirdha, MD Shamsul
Udgivet: (2023)

Machine learning for stress prediction
af: Salehin, Sherajus, et al.
Udgivet: (2023)