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8 events found

Scientific topics: Machine learning 

and

Keywords: HDRUK 

and

City: Bogota  or Copenhagen  or Cambridge  or Norwich  or Rotterdam 

  • Introduction to machine learning with R

    1 - 2 March 2017

    Cambridge, United Kingdom

    Elixir node event
    Introduction to machine learning with R https://tess.elixir-europe.org/events/introduction-to-machine-learning-with-r This course provides a broad introduction to machine learning. Several state-of-the-art machine learning algorithms will be presented, with a focus on classification techniques using KNN, decision trees and random forests. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=1923419&course-title=Introduction%20to%20machine%20learning%20with%20R).'' 2017-03-01 09:30:00 UTC 2017-03-02 17:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning with R

    28 - 29 September 2017

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning with R https://tess.elixir-europe.org/events/an-introduction-to-machine-learning Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Course materials are available [here](https://bioinformatics-training.github.io/intro-machine-learning-2017/). Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2116325&course-title=An%20Introduction%20to%20Machine%20Learning).'' 2017-09-28 08:30:00 UTC 2017-09-29 16:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This introductory course is aimed at biologists with little or no experience in machine learning.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning

    17 - 18 January 2018

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning https://tess.elixir-europe.org/events/an-introduction-to-machine-learning-34557414-af98-4df4-a51d-d8b5af96afcc Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2195228&course-title=An%20Introduction%20to%20Machine%20Learning).'' 2018-01-17 09:30:00 UTC 2018-01-18 17:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This introductory course is aimed at biologists with little or no experience in machine learning.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning

    1 - 2 May 2018

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning https://tess.elixir-europe.org/events/an-introduction-to-machine-learning-38f5ae26-439f-4c3f-9803-fadbefd9ea1a Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2386028&course-title=An%20Introduction%20to%20Machine%20Learning).'' 2018-05-01 08:30:00 UTC 2018-05-02 16:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This introductory course is aimed at biologists with little or no experience in machine learning.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning

    26 - 28 September 2018

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning https://tess.elixir-europe.org/events/an-introduction-to-machine-learning-0a9d6023-6c96-415d-8baf-e38541d7d80e Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2601268&course-title=An%20Introduction%20to%20Machine%20Learning).'' 2018-09-26 12:30:00 UTC 2018-09-28 16:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning

    13 - 15 March 2019

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning https://tess.elixir-europe.org/events/an-introduction-to-machine-learning-bc63dfde-cb44-4637-aa9b-803474afc488 Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=2685309&course-title=An%20Introduction%20to%20Machine%20Learning).'' 2019-03-13 09:30:00 UTC 2019-03-15 17:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
  • Autumn School in Data Science: Machine learning applications for life sciences

    23 - 26 September 2019

    Cambridge, United Kingdom

    Elixir node event
    Autumn School in Data Science: Machine learning applications for life sciences https://tess.elixir-europe.org/events/summer-school-in-biomedical-data-science-best-practices-for-single-cell-analysis-and-machine-learning-applications THIS EVENT IS NOW FULLY BOOKED! This Autumn School aims to familiarise biomedical students and researchers with principles of Data Science. Focusing on utilising machine learning algorithms to handle biomedical data, it will cover: effects of experimental design, data readiness, pipeline implementations, machine learning in Python, and related statistics, as well as Gaussian Process models. Providing practical experience in the implementation of machine learning methods relevant to biomedical applications, including Gaussian processes, we will illustrate best practices that should be adopted in order to enable reproducibility in any data science application. This event is sponsored by [Cambridge Big Data](https://www.bigdata.cam.ac.uk/). The training room is located on the first floor and there is currently no wheelchair or level access available to this level. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book or register your interest by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=3050610&amp;course-title=Autumn%20School%20in%20Data%20Science).'' 2019-09-23 10:30:00 UTC 2019-09-26 14:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Bioinformatics University of Cambridge Bioinformatics Training [] Students and researchers from life-sciences or biomedical backgroundswho haveor will shortly havethe need to apply the techniques presented during the course to biomedical data.The course is open to Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals<span style="color:#FF0000">Please note that all participants attending this course will be charged a registration fee. <span style="color:#0000FF"> Non-members of the University of Cambridge to pay £350. </span style> <span style="color:#0000FF">All Members of the University of Cambridge to pay £175. </span style> <span style="color:#FF0000">A booking will only be approved and confirmed once the fee has been paid in full.</span style> workshops_and_courses [] HDRUK
  • An Introduction to Machine Learning

    2 - 4 October 2019

    Cambridge, United Kingdom

    Elixir node event
    An Introduction to Machine Learning https://tess.elixir-europe.org/events/an-introduction-to-machine-learning-c4f53d48-57b9-468c-bf48-8107350d6d40 Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment. Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes. The training room is located on the first floor and there is currently no wheelchair or level access available to this level. Please note that if you are not eligible for a University of Cambridge [Raven](http://www.ucs.cam.ac.uk/docs/faq/raven/n5) account you will need to book or register your interest by linking [here](http://bioinfotraining.bio.cam.ac.uk/booking-form/?event-id=3043850&amp;course-title=An%20Introduction%20to%20Machine%20Learning).'' 2019-10-02 08:30:00 UTC 2019-10-04 16:00:00 UTC University of Cambridge Craik-Marshall Building, Cambridge, United Kingdom Craik-Marshall Building Cambridge United Kingdom CB2 3AR Machine learning Data mining Bioinformatics University of Cambridge Bioinformatics Training [] This is aimed at life scientists with little or no experience in machine learning and that are looking at implementing these approaches in their research.Graduate studentsPostdocs and Staff members from the University of CambridgeInstitutions and other external Institutions or individuals workshops_and_courses [] HDRUK
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