Beginner’s Guide for Convolutional Neural Network (CNN / ConvNets)

By now, you might be knowing about Machine Learning, a computer science branch that studies the design of algorithms that can learn. Deep learning is a sub-field of machine learning that is inspired by artificial neural networks, which in turn are inspired by biological neural networks. Convolutional Neural Networks are very similar to ordinary Neural... Continue Reading →

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Variants of Gradient Descent

In my earlier post, we have discussed about what is Gradient Descent, how it works and Importance of Learning Rate. Also, we discussed how to make sure that gradient descent is working properly. To recall what was gradient descent, let us define it once again. Gradient Descent is one of the most popular optimization algorithms... Continue Reading →

The outline of Gradient Descent

“A gradient measures how much the output of a function changes if you change the inputs a little bit.” — Lex Fridman (MIT) Gradient Descent is one of the most known optimization techniques. It is the hot topic for every Machine learner and is also one of the vital the topics. Optimization is always one... Continue Reading →

How Neural Networks work and learn?

“Is artificial intelligence less than our intelligence?” —Spike Jonze It is natural to face such questions in mind while seeing that the same piece of calculation computer can do faster than brain. Or sometimes when you play chess on the computer. You might feel that why don't we have such amazing fast powers. But hold... Continue Reading →

Need and Use of Activation Functions

    If you are following my blog, then you might be familiar with ANN till now. Still, let us define Artificial Neural Networks as the powerful and a very strong tool which mimics the human brain. As our brain has neurons which help us send and receive signals through Axons and Synapses, similarly machines... Continue Reading →

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