Machine learning and systems biology in genomics and health

Machine learning design patterns : solutions to common challenges in data preparation, model building, and MLOps
Autor: Lakshmanan, Valliappa
Vydáno: (2020)

Systems biology : properties of reconstructed networks
Autor: Palsson, Bernhard
Vydáno: (2006)

Chemical genomics
Vydáno: (2012)

Machine learning refined : foundations, algorithms, and applications
Autor: Watt, Jeremy, 1983-
Vydáno: (2020)

Functional genomics : methods and protocols
Vydáno: (2017)

Machine learning for decision makers : cognitive computing fundamentals for better decision making
Autor: Kashyap, Patanjali
Vydáno: (2017)

Machine learning : a constraint-based approach
Autor: Gori, Marco, 1957-
Vydáno: (2024)

Machine learning bookcamp : build a portfolio of real-life projects
Autor: Grigorev, Alexey
Vydáno: (2021)

Computational biology : a hypertextbook
Autor: Kelley, Scott T. (Scott Theodore)
Vydáno: (2018)

Personalized machine learning
Autor: McAuley, Julian
Vydáno: (2022)

Bioinformatics and functional genomics
Autor: Pevsner, Jonathan
Vydáno: (2009)

Machine learning : a first course for engineers and scientists
Autor: Lindholm, Andreas, 1989-
Vydáno: (2022)

Evolutionary computation, machine learning and data mining in bioinformatics : 5th European conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007 : proceedings
Vydáno: (2007)

An introduction to computational systems biology : systems-level modelling of cellular networks
Autor: Raman, Karthik, 1981-
Vydáno: (2021)

Machine learning for streaming data with Python : rapidly build practical online machine learning solutions using River and other top key frameworks
Autor: Korstanje, Joos
Vydáno: (2022)

Machine learning from weak supervision : an empirical risk minimization approach
Autor: Sugiyama, Masashi, 1974-
Vydáno: (2022)

Machine learning for embedded system security
Vydáno: (2022)

Úvod do praktické bioinformatiky
Autor: Cvrčková, Fatima, 1966-
Vydáno: (2006)

Machine learning under malware attack
Autor: Labaca-Castro, Raphael
Vydáno: (2023)

The Kaggle book : data analysis and machine learning for competitive data science
Autor: Banachewicz, Konrad
Vydáno: (2022)

Regulatory genomics : RECOMB 2004 international workshop, RRG 2004, San Diego, CA, USA, March 26-27, 2004 : revised selected papers
Vydáno: (2005)

Pattern recognition and machine learning
Autor: Bishop, Christopher M., 1959-
Vydáno: (2006)

Quantum chemistry in the age of machine learning
Vydáno: (2023)

Bioinformatics and functional genomics
Autor: Pevsner, Jonathan, 1961-
Vydáno: (2015)

Fundamentals of systems biology : from synthetic circuits to whole-cell models
Autor: Covert, Markus, 1973-
Vydáno: (2015)

Understanding bioinformatics
Autor: Zvelebil, Marketa
Vydáno: (2008)

Understanding deep learning
Autor: Prince, Simon J. D. (Simon Jeremy Damion), 1972-
Vydáno: (2023)

Scaling machine learning with Spark : distributed ML with MLlib, TensorFlow, and PyTorch
Autor: Polak, Adi
Vydáno: (2023)

Mastering machine learning algorithms : expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work
Autor: Bonaccorso, Giuseppe, 1979-
Vydáno: (2020)

Practicing trustworthy machine learning : consistent, transparent, and fair AI pipelines
Autor: Pruksachatkun, Yada
Vydáno: (2022)

Machine learning with PyTorch and scikit-learn : develop machine learning and deep learning models with Python
Autor: Raschka, Sebastian
Vydáno: (2022)

Machine learning : a concise introduction
Autor: Knox, Steven W.
Vydáno: (2018)

Applied data science using PySpark : learn the end-to-end predictive model-building cycle
Autor: Kakarla, Ramcharan
Vydáno: (2021)

Practical simulations for machine learning : using synthetic data for AI
Autor: Buttfield-Addison, Paris
Vydáno: (2022)

Comparative genomics : RECOMB 2005 international workshop, RCG 2005, Dublin, Ireland, September 18-20, 2005 : proceedings
Vydáno: (2005)

Comparative genomics : RECOMB 2006 international workshop, RCG 2006, Montreal, Canada, September 24-26, 2006 : proceedings
Vydáno: (2006)