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.

• 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.