Have you ever seen a beautiful flower and wondered what kind of flower it is? Well, you're not the first, so let's build a way to identify the type of flower from a photo!

For classifying images, a particular type of deep neural network, called a convolutional neural network has proved to be particularly powerful. However, modern convolutional neural networks have millions of parameters. Training them from scratch requires a lot of labeled training data and a lot of computing power (hundreds of GPU-hours or more). We only have about three thousand labeled photos and want to spend much less time, so we need to be more clever.

In this Project, Using transfer learing we will classify each image in a dataset into 5 Classes

The dataset contains Images of 5 different flowers. claases are :

1.Dandelion

2.Daisy

3.Tulips

4.Sunflowers

5.roses

After training the model for just 6 epochs, the accuracy achieved was 94%

Testing our model on test data, The Results were satisfying.