In this data science and machine learning project, we are classifing sports personalities. (The concept can be use to predict faces of different people n generel). Here we are restricting our classification to only 5 people:

1. Maria Sharapova
2. Serena Williams
3. Virat Kohli
4. Roger Federer
5. Lionel Messi

Here is the folder structure,

• model: Contains python notebook for model building
• google_image_scrapping: code to scrap google for images
• images_dataset: Dataset used for our model training
• JSON file: Which stores best predicted model

Technologies used in this project:

• Python
• Numpy and OpenCV for data cleaning
• Matplotlib & Seaborn for data visualization
• Sklearn for model building
• Jupyter notebook as IDE

Machine learning concepts used here are:

• Logistic Regression
• Support Vector Machine
• Random Forest
• K Fold Cross Validation
• Hyper Parameter Tuning (Grid Search CV)
• Joblib and Pickle

PS: This is my first ML project. And I am really glad that with the help of this project I could learn the crux of ML algoritms. I am excited and lookimg forward to apply this concept of image classification in future projects in a much more interesting concept.