A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed graph along a sequence.

Regularization is a technique which is used to solve the overfitting problem of the machine learning models.

L1 and L2 are two loss functions in machine learning which are used to minimize the error.

Bias is one of the important terminologies in machine learning. Often we add bias while creating any model in the artificial neural network.

Feature engineering is the process of using domain knowledge of the data to create features that make machine learning algorithms work. If feature engineering is done correctly, it increases the predictive power of machine learning algorithms by creating features from raw data that help facilitate the machine learning process. Feature Engineering is an art.

Yet another article on - Introduction To Machine Learning. Believe me, this article is going to be the simplest introduction to the term Machine Learning. So, let’s start without wasting our time.

An open-source machine learning framework for everyone. As I believe, when we know the internals of a library, we can get the most out of it. And we feel much more confident while working with that library. Today, TensorFlow is being used by top companies like Google, Uber, Airbnb, Nvidia, Dropbox, etc.

TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices.

Reinforcement Learning is a type of Machine Learning where an agent learns how to behave in an environment by performing certain actions and learning from the results of those actions.