Types of Machine Learning Models

Types of Machine Learning Models

Carlos Salas

Portfolio Manager and Data Scientist

The choice machine learning model is dependent on the specifics of the problem and the data at hand. Join Carlos Salas as he guides you through the differences between supervised and unsupervised machine learning models, including principal component analysis, generalised linear models and support vector machines.

The choice machine learning model is dependent on the specifics of the problem and the data at hand. Join Carlos Salas as he guides you through the differences between supervised and unsupervised machine learning models, including principal component analysis, generalised linear models and support vector machines.

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Types of Machine Learning Models

9 mins 3 secs

Overview

Broadly speaking, a model is a simplified representation of reality. The researcher always tries to develop a model that can either represent reality accurately or, at the very least, determine a set of conditions or assumptions that will allow them to control the testing of the model as scientists do in laboratories. There are two main types of machine learning models: supervised and unsupervised. We have to pick the right tool for the job when dealing with complicated financial datasets.

Key learning objectives:

  • Define a model

  • Understand the difference between supervised and unsupervised models

  • Outline how different models can solve the same problem

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Summary
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Expert
Carlos Salas

Carlos Salas

Carlos Salas is a professional investor passionate about the lifelong development of an investment process that blends man and machine. Over the last 15 years, he has worked in investment roles for firms such as Santander AM, BNP Paribas, Jefferies, and LCAM. He is currently pursuing three careers simultaneously - as an investment manager, consultant and lecturer.

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