This is a 30 days machine learning bootcamp. There are day wise practice projects related to the machine learning.

Feel free to customize and expand upon the project to suit your specific requirements.

1. Advertisment Sale Prediction / dataset

   • Using Logistic Regression

2. Handwritten Digit Recognition

   • Using K- Nearest Neighbor Classifier

3. Titanic Survival Prediction / dataset

   • Using Gaussian Naive Bayes Algorithm

4. Leaf Species Detection

   • Using Decision Tree Classifier

5. Digit Recognition / dataset

   • Using Random Forest Classifier

6. EDA on Superstore dataset / dataset

7. Breast Cancer Prediction / dataset

   • Using six algorithms:
     
     1. Linear Discriminant Analysis:
     
     2. Logistic Regression:
     
     3. Decision Tree Classifier:
     
     4. K- Nearest Neighbor Classifier:
     
     5. Gaussian Naive Bayes Algorithm:
     
     6. Support Vector Machine

8. Exam Marks Prediction / dataset

   • Using Linear Regression

9. Salary Prediction / dataset

   • Using Polynomial Regression

     

   • Equation of the Polynomial Regression Model:

     1. Simple Linear Regression equation: y = b0+b1x

     2. Multiple Linear Regression equation: y= b0+b1x+ b2x2+ b3x3+....+ bnxn

     3. Polynomial Regression equation: y= b0+b1x + b2x2+ b3x3+....+ bnxn

10. Used Car Price Prediction / dataset

11. Market Basket Analysis / dataset

• Using APRIORI AND ECLAT

12. WebAd. Optimization using Reinforcement Learning / dataset

• Using Reinforcement Learning

13. Ad _placement Optimization using Reinforcement Learning / dataset

• Using Reinforcement Learning