Machin Learining Projects
->Data Preprocessing
- Data Preparation is an important part of Data Science. It includes two concepts such as Data Cleaning and Feature Engineering. These two are compulsory for achieving better accuracy and performance in the Machine Learning and Deep Learning projects.
- Data Preprocessing is a technique that is used to convert the raw data into a clean data set. In other words, whenever the data is gathered from different sources it is collected in raw format which is not feasible for the analysis.
->Regression based projects
1.Boston House Price:
- Predicts the price of houses in boston
- It is based on Simple Linear Regression Algorithm
2.Slary Prediction model:
- Predicts the salary of an employee based on experience
- It is based on Simple Linear Regression
3.Profit pediction model:
- Predicts the profit of a startup based on R&D spend,Administration and marketing
- It is based on Multiple Linear Regression
4.Predicting Previous salary of new Employee:
- This model is used to predict the previous salary of new employee to check wheter the new employee is saying truth about his/her salary
- It is based on Polynomial Linear Regression
->Classification Based Projects
1.Written own classifer:
- This project uses iris dataset
- This project uses classifier written from scratch
- The classifier uses euclidean fornula to calculate the distance of test point from train points
- The classifier gives accuracy around 0.96
2.Social Networking Ads:
- This model is used to predict whether the user will buy the product based on the advertisement of that product
- It is based on Logistic Regression