Convolutional Neural Networks Mastery – Deep Learning – CNN

With the Deep learning making the breakthrough in all the fields of science and technology, Computer Vision is the field which is picking up at the faster rate where we see the applications in most of the applications out there.

Be it, Facebook’s image tagging feature, Google Photo’s People Recognition along with Scenery detection, Fraud detection, Facial Recognition, We are seeing the Computer Vision Applications out there

A typical & basic operation we perform is – Convolution Operations on Images, where we try to learn the representations of the image so that the computer can learn the most of the data from the input images.

In this course,

It is said as,

We are going to prefer learning – PyTorch for these Reasons:

1. It is Pythonic
2. Easy to Learn
3. Higher Developer Productivity
4. Dynamic Approach for Graph computation – AutoGrad
5. GPU Support for computation, and much more...

In this course,  We are going to implement Step by Step approach of learning:

1. Understand the Basics of PyTorch
2. Learn to Code in GPU & with a guide to access free GPU for learning
3. Learn Auto Grad feature of PyTorch
4. Implement Deep Learning models in Pytorch
5. Learn the Basics of Convolutional Neural Networks in PyTorch(CNN)
6. Practical Application of CNN’s on Real World Dataset