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What is a neural network?: Very simple explanation of a neural network using an analogy that even a high school student can ...

I asked a couple of my friends this question: What is the difference between Machine Learning and Deep Learning and majority of ...

RNN or Recurrent Neural Network are also known as sequence models that are used mainly in the field of natural language ...

This video gives a very simple explanation of a chain rule that is used while training a neural network. Chain rule is something that ...

AI vs ML vs DL vs Gen AI, these terms can be confusing to understand. In this short video, I will explain the difference between ...

Are you planning to deploy a deep learning model on any edge device (microcontrollers, cell phone or wearable device)?

Machine learning models don't understand words. They should be converted to numbers before they are fed to RNN or any other ...

This video explains four reasons why deep learning has become so popular in past few years. In this deep learning tutorial python ...

Bi directional RNNs are used in NLP problems where looking at what comes in the sentence after a given word influences final ...

Activation functions (step, sigmoid, tanh, relu, leaky relu ) are very important in building a non linear model for a given problem.

Are you using flask or Fast API to serve your machine learning models? tf serving is a tool that allows you to bring up a model ...

Derivatives and partial derivatives are important concepts that we need to understand in order to gain knowledge on how neural ...

YOLO (You only look once) is a state of the art object detection algorithm that has become main method of detecting objects in the ...

Vanishing gradient is a commong problem encountered while training a deep neural network with many layers. In case of RNN ...

In this video, we will see how you can think of a logistic regression as a neuron. We will use insurance dataset as a sample and ...

Overfitting and underfitting are common phenomena in the field of machine learning and the techniques used to tackle overfitting ...

Matrix fundamentals are essential to understand how deep learning works. In this video we will go over what is matrix, matrix ...

In this video we will understand how K nearest neighbors algorithm work. Then write python code using sklearn library to build a ...

Simple Explanation of GRU (Gated Recurrent Units): Similar to LSTM, Gated recurrent unit addresses short term memory problem ...

LSTM or long short term memory is a special type of RNN that solves traditional RNN's short term memory problem. In this video I ...