Types of layers used to build Convolutional Neural Networks in Deep Learning and Computer vision.

Artificial Intelligence is witnessing tremendous growth bridging the gap between humans and machines. One of the domains in such an area is computer vision. The agenda for this field is to allow machines to see…

Convolution neural network is the major building block of deep learning, which helps in image classification, object detection, image recognition, etc of computer vision tasks. We use many convolution operation techniques that we will discuss in this article.

Have you ever used photo editing tools?

Which makes your image sharper…

MLflow simplifies tracking and reproducibility for tuning workflows

Hyperparameter tuning and optimization is a powerful tool in the field of AutoML. Tuning these configurations can dramatically improve model performance. However, hyperparameter tuning can be computationally expensive and slow.

If you have a large network like VGG, Resnet, etc. trying out every parameter exhaustively and then choosing the best…

Batch normalization and dropout act as a regularizer to overcome the overfitting problems in a Deep Learning model.

Have you come across a large dataset that causes overfitting?

One of the reasons for overfitting is large weights in the network. A network with large network weights can be a sign of an unstable network where small changes in the input can lead to large changes in the output…

aditi kothiya

Data science | Deep Learning | Computer Vision | Machine learning

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store