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This video is really a conclusion to the previous one where Iintroduced a few modern best practices and concepts for creating ...

"Dr. R.R.Dube Professor Electronics and Telecommunication Engineering Walchand Institute of Technology, Solapur"

In this video, we take a look at Feature Pyramid Networks (FPN). What is it? How does it work? Why they are so useful in computer ...

Let's visualize what a convolution neural network actually learns, their feature maps and more! ABOUT ME ⭕ Subscribe: ...

Lecture 13: Introduction to Convolutional Codes Topics covered: Introduction to Convolutional Codes Instructor: Prof.

In this video, we take a look at depthwise separable convolutions. What is it? How does it work? Why do it? Code included!

In this video, we take a look 1x1 convolutions (point wise convolutions) and demonstrate what they are, why they are useful, ...

Lecture 14: Introduction to Convolutional Codes Topics covered: Introduction to Convolutional Codes Instructor: Prof.

In this video, we will explore the concept of zero padding in Keras convolutional layers, a crucial technique for enhancing the ...

In this video I look at the two basic approaches that you can use to represent word order for processing text with a deep network ...

Lecture 05: Introduction to Binary Block Codes Topics covered: Introduction to Binary Block Codes Instructor: Prof. David Forney ...

In this video, we take a look the ResNet network. What is it? Why is it better than some of the shallower networks that came before ...

In this video, we take a look the VGG network architecture. What is it? Why is it so deep? How do we code it out? How well does it ...

Lecture 06: Convolutional Codes Description: This lecture starts with historical applications of error control and convolutional ...

Lecture 24: Linear Gaussian Channels Topics covered: Linear Gaussian Channels Instructor: Prof. David Forney Source: OCW ...

In this video I continue with our talk about the two basic approaches that you can use to represent word order for processing text ...

Lecture 19: The Sum-Product Algorithm Topics covered: The Sum-Product Algorithm Last session of the course Instructor: Prof.

In this video, we take a look at what the deep layers of a convolution neural network actually learn with some neat visuals.

Lecture 16: Trellis Representations of Binary Linear Block Codes Topics covered: Trellis Representations of Binary Linear Block ...

Lecture 22: Lattice and Trellis Codes Topics covered: Lattice and Trellis Codes Instructor: Prof. David Forney Source: OCW MIT ...