Course: Learning Machine Learning 2018 - Colombia - Exterior - Universidad del Rosario (Summer School) - I43843

Home>Cursos>Programación>Colombia>Course: Learning Machine Learning 2018 - Colombia - Exterior
 
Course: Learning Machine Learning 2018
Método: Presencial
Lugar:
Tipo: Cursos
Enlaces Patrocinados
Loading...

Solicita información sin compromiso
Universidad del Rosario (Summer School)

Course: Learning Machine Learning 2018 - Colombia - Exterior

Nombre
Apellidos
E-Mail
Titulación
Provincia
Teléfono
Código Área Ej: 11
 
 
 
 
Teléfono Fijo Ej: 54544444
 
 
 
 
Mi teléfono es:
Fijo
Celular
Para enviar la solicitud debes aceptar la política de privacidad
* Campos obligatorios

En breve un responsable de Universidad del Rosario (Summer School), se pondrá en contacto contigo para informarte.
Por favor, rellená todos los campos correctamente
Course: Learning Machine Learning 2018 - Colombia - Exterior Comentarios sobre Course: Learning Machine Learning 2018 - Colombia - Exterior
Contenido:
Course: Learning Machine Learning 2018.

Language: English.

Call for projects.

This is a form that will allow you to tell us about a possible project that you have in mind for which Machine Learning can be useful. 
  
Description.

Learning Machine Learning 2018 (LML18) is a 6-day summer school organized by the Department of Applied Mathematics and Computer Science, Universidad del Rosario with the support of Universidad de Los Andes and the Institute for Applied Computational Science (IACS) of Harvard University. LML18 is an event that will bring together beginners and experts in Machine Learning (ML) and Data Science (DS) in a multilevel school that will cover basic concepts in these areas, but will also provide multidisciplinary spaces for participants to develop projects based on real datasets from academia, industry, or the public sector. During the first four days, basic courses and intermediate workshops will be offered on modern methodologies of ML, such as supervised and unsupervised classification, regression, and the basics of artificial neural networks. The last two days will be hack days in which participants will have the chance to apply these methods to solve real problems provided by companies, research groups, or the participants themselves.
  
Target public.

LML18 is a multilevel school intended for a wide audience of people interested in ML. This includes those with limited or very basic experience on statistics, python programming and machine learning, those who own large and complex datasets whose analysis requires state-of-the-art methods, and also those with intermediate to advanced experience in ML who would like to update their tools and create collaborations. Basic knowledge of probability, statistics and Python is desirable, but even those without this experience should be able to follow the course (as long as they like data, statistics, and programming).
  
Methodology.

Each of the first four days of LML18 will have two plenary lectures (with exercises), and two practical unconferences or labs to practice with specific tools and problems. The last two days will be hack days, in which participants will work on specific projects involving real data. Multilevel working groups will be formed to work on those specific problems. Public and private institutions will also have a chance to present some of their specific data problems and challenges.

Schedule.

  • Dates: July 23 to July 28, 2018
  • Schedule: Monday to Saturday 8:00 a.m. – 6:00 p.m.
  • Venue: Claustro, Universidad del Rosario
  • Duration: 48 hours
  • Type: Course
  • Credits: 3 UR credits (5.1 ECTS)
  • Language: English
  • Organized by: Department of Applied Mathematics and Computer Science, Universidad del Rosario – Universidad de los Andes - Institute for Applied Computational Science at Harvard University.
Contents:   
 
CONFERENCES.

Introduction to Machine learning and probability.

Topics: 

  • Introduction to ML. 
  • Laws of probability. 
  • Bayes rule. 
  • Distributions. 
  • Maximum likelihood estimation.
Date: 23/07/2018.
Schedule:  8:00 - 10:00 | 10:30 - 12:30.

Optimization.

Topics:

  • Introduction to optimization. Convexity.
  • Stochastic gradient descent.
  • Newton’s method.
  • Constrained optimization.
Date: 24/07/2018
Schedule:  8:00 - 10:00 | 10:30 - 12:30.

Machine learning I.

Topics:

  • Classification. Generative models. Logistic regression.
  • Support vector machines.
  • Maximum margin. Nearest neighbors.
  • Maximum margin. Nearest neighbors.
Date: 25/07/2018
Schedule: 8:00 - 10:00 | 10:30 - 12:30.

Machine learning II.

Topics:

  • Validation
  • Cross-validation
  • Unsupervised methods
  • Clustering
Date: 26/07/2018
Schedule: 8:00 - 10:00 | 10:30 - 12:30.

UNCONFERENCES.

Unconferences day I.

Topics: Python I: Basics
Date: 23/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Introduction to MCM (Metropolis)
Date: 23/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Distributions in the real world
Date: 23/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Unconferences day II.

Topics: Python II: Theano, scikit-learn.
Date: 24/07/2018.
Schedule: 2:00 p.m. | 3:30 p.m.

Topics: Simulated annealing
Date: 24/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Genetic algorithms
Date: 24/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Linear regression
Date: 24/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Unconferences day III.

Topics: Support vector machines
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.

Topics: Classifying the MNIST dataset
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Bayesian linear regression
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Introduction to neural networks
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Unconferences day IV.

Topics: Regularization
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.

Topics: PyMC3
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.

Topics: K-means
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Model selection: regularization
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.
 
Topics: Bayesian inference with PyMC3
Date: 25/07/2018
Schedule: 2:00 p.m. | 3:30 p.m.

*May be subject to change.

Discounts:

The price is subject to change depending on the exchange rate.
 
Early bird discount: 10% discount on the course fees until July 8, 2018.

Rosario community discount: A 10% discount on enrollment fees. This may be received in addition to the early bird discount.

Discount for students, professors and graduates from international institutions: 10% discount on the course fees, which can be accumulated and/or combined with the benefit for early bird discount.

General Terms and Conditions:

The University reserves the right to cancel a course or program if the minimum financial resources needed to open the course or program are not met. In such event, the University will refund 100% of the amount paid by the students in the currency of origin by electronic transfer (wire transfer) to the bank account they have provided. The transfer will be made within five business days following the date that the participant's bank account information was received.

In the event that a participant decides not to take the course or program and has already paid the corresponding enrollment amount, provided the course has not commenced, the participant may request the refund of his/her money. In this case, the University will make an electronic transfer in the amount of 90% of the amount that was originally received; 10% of which will be retained for the reimbursement of administrative and banking expenses incurred by the university. The refund will be made in the original payment’s currency of origin within 8 business days following receipt of the request to withdraw, cancel and receive a refund.
Otra formación relacionada con Cursos de Programación:
Nueva Búsqueda
Buscar