This is the first article in the series of articles on “Creating a Neural Network From Scratch in Python”. Introduction Have you ever wondered how chatbots like Siri, Alexa, and Cortona are able to respond to user queries? Or how the autonomous cars are able to drive themselves without any human help? All of these fancy products have one thing in common: Artificial Intelligence (AI). It is the AI which enables them to perform such tasks without being supervised or […]

This is the second article in the series of articles on “Creating a Neural Network From Scratch in Python”. If you are absolutely beginner to neural networks, you should read Part 1 of this series first (linked above). Once you are comfortable with the concepts explained in that article, you can come back and continue with this article. Introduction In the previous article, we started our discussion about artificial neural networks; we saw how to create a simple neural network […]

This is the third article in the series of articles on “Creating a Neural Network From Scratch in Python”. If you have no prior experience with neural networks, I would suggest you first read Part 1 and Part 2 of the series (linked above). Once you feel comfortable with the concepts explained in those articles, you can come back and continue this article. Introduction In the previous article, we saw how we can create a neural network from scratch, which […]

Introduction Machine learning and deep learning algorithms learn from data, which consists of different types of features. The training time and performance of a machine learning algorithm depends heavily on the features in the dataset. Ideally, we should only retain those features in the dataset that actually help our machine learning model learn something. Unnecessary and redundant features not only slow down the training time of an algorithm, but they also affect the performance of the algorithm. The process of […]

Introduction In the previous article, we studied how we can use filter methods for feature selection for machine learning algorithms. Filter methods are handy when you want to select a generic set of features for all the machine learning models. However, in some scenarios, you may want to use a specific machine learning algorithm to train your model. In such cases, features selected through filter methods may not be the most optimal set of features for that specific algorithm. There […]

Introduction Time series analysis refers to the analysis of change in the trend of the data over a period of time. Time series analysis has a variety of applications. One such application is the prediction of the future value of an item based on its past values. Future stock price prediction is probably the best example of such an application. In this article, we will see how we can perform time series analysis with the help of a recurrent neural […]