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MOOC Machine learning and big data for bioinformatics. 2 Edition
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ML_bioinformatica_2ed
Modulo 3: Data Science and Machine Learning
3.3.- Unsupervised Learning
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3.3.- Unsupervised Learning
3.3 Unsupervised Learning
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Last modified: Wednesday, 16 February 2022, 10:38 AM
◄ Video 3.3
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CERTIFICADO OFICIAL
Module 1 Questionnaire
Module 2 Questionnaire
Module 3 Questionnaire
Module 4 Questionnaire
Module 5 Questionnaire
Module 6 Questionnaire
Module 7 Questionnaire
Module 8 Questionnaire
Final Questionnaire
Module 1 discussion forum
Video 1.1
1.1. Bioinformatics: what, why, and how?
Video 1.2
1.2.- Applications in Bio-Sciences and Bio-Health
Video 1.3
Module 2 discussion forum
Video 2.1
2.1.- The problem: How to obtain and prepare the data?
Video 2.2
2.2.- Pre-processing and exploratory analysis
Video 2.3
2.3.- Functional annotation analysis
Module 3 discussion forum
Video 3.1
3.1.- What, how and why?
Video 3.2
3.2.- Supervised Learning
Video 3.3
Module 4 discussion forum
Video 4.1
4.1.- Regression: What, what for and how?
Video 4.2
4.2.- Classical Regression Methods
Video 4.3
4.3.- Machine Learning methods for regression
Module 5 discussion forum
Video 5.1
5.1.- Classification: What, what for and how?
Video 5.2
5.2.- Standard methods in classification
Video 5.3
5.3.- Advanced methods in classification
Module 6 discussion forum
Video 6.1
6.1 Clustering and Association Rules: What, what for and how?
Video 6.2
6.2 Clustering
Video 6.3
6.3 Association Rules
Module 7 discussion forum
Video 7.1
7.1.- Introduction to Big Data
Video 7.2
7.2.- Introduction to Spark using Python
Video 7.3
7.3.- Machine Learning in Spark: MLib
Video 7.4
7.4.- Classification, Regression, Clustering and Association Rules in Spark
Module 8 discussion forum
Video 8.1
8.1 How to use KNIME? - Workflows
Video 8.2
8.2 How to solve a problem with KNIME?
Video 8.3
8.3 Supervised Learning: Regression and Classification in Knime
Video 8.4
8.4 Unsupervised Learning: Clustering and Association Rules in Knime
Datasets example
Example data flows
How to install KNIME
GLOSARIO
GLOSSARY
Presentation and Welcome
Guide
Module 4 discussion forum ►
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