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Machine Learning

Machine Learning


This course will understand the concepts needed to perform processes Machine Learning, this branch of artificial intelligence that aims to develop techniques that allow computers to learn.

Machine Learning projects create algorithms that can generalize and recognize behavior patterns from information provided by way of example ( training). Machine Learning techniques are used among others in the following areas: Medicine, Bioinformatics, Marketing, Natural Language Processing, Image Processing, Machine Vision, Spam Detection.

Machine Learning

Target audiences

  • ICT professionals: Consultants BI, Scientific Data.
  • Professionals of Applied Sciences: Mathematics, Statistics, Physics.


  • Methodology: The course intersperses theoretical parts where fundamental concepts are taught to understand the practical exercises taught.
  • Requirements: Basics: Linear Algebra, calculus and probability theory.


1. Introduction to Machine Learning
  • Definition of a process flow and Machine Learning
  • Apprentice supervised and unsupervised
  • Types of algorithms: clustering, classification, regression,...
  • Measuring quality of an algorithm: Confusion Matrix, ROC curve (AUC).
2. Extracting data structure: Clustering
  • K-Means
  • Gaussian Mixture Models (GMM)
3. Recommendation Systems
  • Singular value decomposition of a matrix (SVD)
  • Collaborative filtering
  • Recommendation using SVD (Choose movies for a user)
  • Recommendation using SVD (Choose users a campaign promoting a film)
4. Classification
  • Linear regression
  • Logistic regression
  • Fraud detection with logistic regression
5. Deep Neural Networks and Learning
  • Introduction to Neural Networks
  • Simple perceptron
  • multilayer perceptron
  • Backpropagation training algorithm (backpropagation)
  • Restricted Boltzmann Machines (RBMS)
6. Election Systems
  • Test A / B (Experiment 2 groups)
  • Experiment slot machine with several levers
7. Natural Language Processing
  • Natural Language Processing with Python (NLTK)
  • Useful features for semantic analysis
  • Generation vocabularies
  • Tokenization: Step text phrases
  • Sentiment analysis on movie reviews


Machine Learning Training

  • Online

Date: Del 01 Dec. - 02 Dec. 2016.

Schedule: 16:00H - 21:00H (CEST - Madrid)

Place: Plataforma web con profesor

Price: 95€ / person

Payment: Paypal or Wire transfer (Ask)

Machine Learning Training

  • Workshop

Date: Del 10 Nov. - 11 Nov. 2016.

Schedule: 9:00H - 14:00H and 15:30H - 18:30H

Place: Av. de Brasil, 17, 16º A-B. Madrid

Price: 575€ / person

Payment: Paypal or Wire transfer (Ask)


Ajustamos cada curso a sus necesidades.

Nuestra oficina en Madrid

Do you need a training?. We may offer a wide training catalog based on platform and software tools such as Pentaho, Talend, Mondrian, Ctools.