README.md

Supervised Machine Learning:

Supervised Machine Learning is all about training lots of preprocessed input data (past data) with labels, evaluate performance of trained model and after getting satisfactory performance using that model to perform prediction on new data. If labels or output is continuous value then it is Regression and if these are categorical or discrete value then it is classification.

Some Basic Supervised ML Algorithms:

1. Linear Regression
2. Logistic Regression
3. Decision Tree
4. Random Forest
5. K Nearest Neighbour
6. Naive Bayes
7. Support Vector Machine

Description:

Here i have used ScikitLearn machine learning library to build some simple and basic models using different algorithms. Steps involved to build ML models:

1. Import Data
2. Data Analysis
3. Data Cleaning
4. Model training & testing
5. Performance evaluation

ScikitLearn installation using pip:

pip install sklearn