Different Machine Learning Types: Supervised, Unsupervised and Reinforcement Learning
Understanding the various types of machine learning is a fundamental building block for working with ML. This article will provide a detailed look at three primary approaches: supervised learning, unsupervised learning, and reinforcement learning.
Predicting Real Estate Prices
Price Prediction
Insurance Valuation
Reducing the Number of Features While Preserving Important Information.
PCA (Principal Component Analysis) - visualizing multi-dimensional data
t-SNE - visualizing complex data
Frequently asked questions
What are the different types of Reinforcement Learning?
Reinforcement learning encompasses various approaches, including Q-learning and Deep Q-Networks.
What is the focus on evaluating the quality of states and actions (Q-?
The focus in Q-learning and Deep Q-Networks is on evaluating the quality of states and actions to determine optimal policies.
What is Policy-Based Learning?
Policy-based learning directly learns a policy without explicitly estimating value functions.
What is direct learning of the policy without evaluating values?
This refers to Policy Gradient methods, which optimize the policy directly based on sampled transitions.
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Everything above runs in your browser — open Decision Tree Live and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.