In this blog post we will learn about CUDA programming, difference between C and CUDA programming and how it is efficient. Generally these days laptop and computers have shared CPUs and GPUs in-built, but we will learn how to use Google Colabs for CUDA programming.

In this blog post we will be learning about two of the very recent activation functions Mish and Swift. Some of the activation functions which are already in the buzz. Relu, Leaky-relu, sigmoid, tanh are common among them. These days two of the activation functions Mish and Swift have outperformed many of the previous results by Relu and Leaky Relu specifically. Let us move on and get more into it!!

In this blog post we will be learning about Generative and Discriminiative models. Suppose that we have one model which can learn things in-depth and thoroughly and we have another model which can learn to identify only the differences between the things it sees.

In this blog post we will be focusing on MobileNet v1 using Separable Convolutions. Also we will focus on the differences between normal convolutions and separable convolutions and differences between their memory consumptions.

In this blog post we will be focusing on the working of EfficientNet. We have seen that how CNN can be used for so many different tasks. Also we know that, once we increase the depth of CNNs they can detect the high level features more easily and with greater accuracy. But increasing the depth (adding more layers to CNN) has some major problems:-