1.)Music Genre Classification
There are 10 genres each containing 100 songs. We need to predict the genre based on the audio.
Extracted 26 features from audio files and built a artificial neural network which predicts the genre for a given audio file
2.) Histopathologic Cancer Detection
There are almost 2.2 lakh labelled images in which 60% images have cancer, 40% images have no cancer
Built a CNN Model 2 predict whether the image has cancer tissue or not
3.) U_NET Algorithm
We trained the unet with (128,128,3) rgb image as input and (128,128,1) mask as output
So, if we give rgb image, it needs to predict the mask image
Pixel level classification thats y 1*1 convolution at the end