# Introduction

* Machine Learning (ML) is a type of Artificial Intelligence (AI).
* ML allows computers to automatically learn and improve from experience without being explicitly programmed to do so.&#x20;
* Using ML, computers learn from data to discover patterns and make predictions.
* Machine learning is a technique that uses mathematics and statistics to create a model that can predict unknown values. - **MS**

## Stages in Machine Learning

1.  Machine Learning Model

    A block of code to used to solve different problems eg. Linear Regression
2.  Model Training Algorithm

    an iterative process

    * determine what changes need to be made
    * make small changes to the model
3.  Model Inference Algorithm

    using a trained model to generate predictions

## Types of Machine Learning

1.  **Supervised Learning**

    In **supervised learning**, every training sample from the dataset has a corresponding label or output value associated with it. As a result, the algorithm learns to predict labels or output values.
2.  **Unsupervised Learning**

    In **unsupervised learning**, there are no labels for the training data. A machine learning algorithm tries to learn the underlying patterns or distributions that govern the data.
3. **Reinforcement Learning**\
   In **reinforcement learning**, the algorithm figures out which actions to take in a situation to maximize a reward (in the form of a number) on the way to reaching a specific goal.
