Photo by Lenin Estrada on Unsplash |

**What is Machine Learning**

Machine Learning comprises of various techniques and algorithms
to make a constant corrective program. It differs from hardwired programming in
a manner that the later is a set of instructions to perform a fixed task while
Machine Learning is not just a set of instructions programmed but incorporated
with data in such a way that results after every run can be different and more
accurate.

**What are the various Machine Learning Algorithms**

Machine Learning is broadly classified into Supervised and
Unsupervised Learning. Supervised Learning incorporates data sets that are labeled
e.g. when we use the dataset of patients suffering from a particular disease in
a machine learning problem and we have their set of symptoms at our hand, then,
the case can be called supervised learning. On the other hand, the learning
procedures involving unlabelled data come under unsupervised learning. Various
categories of ML Algorithms are summarized below:

- Supervised Learning
- Regression
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Non-Linear Regression
- Ridge Regression
- Lasso Regression
- Classification
- Logistic Regression
- Linear Discriminant Analysis
- Quadratic Discriminant Analysis
- Decision Trees
- Support Vector Machines
- Random Forests
- Unsupervised Learning
- K-Means Clustering
- DBSCAN
- Principal Component Analysis
- PAM

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