Pattern Recognition Training Course

Course Code

datamodeling

Duration

35 hours (usually 5 days including breaks)

Requirements

  • Understanding of statistics
  • Familiarity with multivariate calculus and basic linear algebra
  • Some experience with probabilities

Overview

This course provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.

The course is interactive and includes plenty of hands-on exercises, instructor feedback, and testing of knowledge and skills acquired.

Audience
    Data analysts
    PhD students, researchers and practitioners

 

Course Outline

Introduction

Probability theory, model selection, decision and information theory

Probability distributions

Linear models for regression and classification

Neural networks

Kernel methods

Sparse kernel machines

Graphical models

Mixture models and EM

Approximate inference

Sampling methods

Continuous latent variables

Sequential data

Combining models

 

Bookings, Prices and Enquiries

Guaranteed to run even with a single delegate!

Private Classroom

From £7250

Private Remote

From £6500 (100)

Public Classroom

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