minor project - Image classification on apples and bananas

1. First thing first collect the data(2 or more categories images)

2. You can collect images from anywhere like google images or Kaggle

3. Then Preprocess the data:

• Scale down the images to a specific value (like (150,150,3)every image)
• Convert into a Single Dimension Array (Vector) – Flattening of an Image
• Creating DataFrame by iterating through the Images

4. Now use machine learning classification algorithms like SVM, K means, logistic regression etc.

5. Now check the accuracy for the model if it is less then try using other algorithms to improve the score

 

My project link:- github