## Types of machine learning algorithm

**What is machine learning?**

*Machine Learning refers to the techniques involved in dealing with vast data in the most intelligent fashion (by developing algorithms) to derive actionable insights.*

- Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data.
- Such algorithms operate by building a model based on inputs
- and using that to make predictions or decisions, rather than following only explicitly programmed instructions.

**How do we teach machines?**

- Data as Input
- Text files, Spreadsheets, SQL Databases

- Representation of the data in structural format through the chosen algorithm
- The elementary learning happens here

- Generalization
- The practical application happens here where the learning from the previous steps is used to develop an insight

**Types of machine learning algorithm**

**Supervised machine learning algorithm**- Linear / logistic regression
- Linear discriminant analysis
- Decision trees
- Support Vector machines
- Naive Bayes
- k-nearest neighbor algorithm
- Neural Networks (Multilayer perceptron)

**Unsupervised machine learning algorithm**- K means clustering
- Hierarchical clustering
- Principle component analysis

**Reinforcement machine learning algorithm**- Deep Q-learning algorithm
- Markov decision process