Machine Learning: The + Relevant pt. 3

Cath Sandoval
Copywritter

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First of all, promises are promises! We continue with this series of articles based on the most relevant and interesting questions about Machine Learning.

Without further ado, let’s get started!

These are some of the most popular machine learning algorithms:

  • Neural networks.
  • Decision trees (Decision Trees).
  • Probabilistic networks.
  • Nearest Neighbor.
  • Support vector machines (Support vector machines).

We can also find some techniques in Machine learning:

What are the different techniques/approaches to algorithms in machine learning?
  • Supervised.
  • Unsupervised.
  • Semi-supervised.
  • By reinforcement.
What is the standard approach to partitioning data in supervised learning?

Certainly the standard approach to supervised learning is to divide the set of examples into the training set and the test set (one can also mention the validation set).

What is the “training set” and the “test set”?

1.First, the training set is a set of examples given to the learner.

2.Finally, the test set is used to test the accuracy of the hypotheses generated by the learner, and is the set of examples that are hidden from the learner.

What is the role of “unsupervised learning”?
  • Finding clusters of data.
  • Get low-dimensional representations of the data.
  • Finding interesting directions in the data.
  • Detect interesting coordinates and correlations.
Examples of the use of ‘Supervised Learning
  • Classifications.
  • Recognition of images.
  • Speech recognition.
  • Regressions.
  • Time series prediction.

Finally, we leave you cordially invited to our last article of this series as interesting as Machine learning and its most relevant questions.

Therefore, we reaffirm that Machine learning is extremely important for LISA Insurtech and the quality of its processes and services. Therefore, we share with you the direct access to our web DEMO, where you can see for yourself the capabilities of our cutting-edge technology.

Continue Reading...

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