Machine Learning algorithms need properly formatted data to give good predictions. Preparing data for a machine learning project can be difficult and can take most of the time (sometimes up to 80%). But it need not be so. In this article, you will learn a very practical approach on how to prepare data for machine […] ...

Deep Learning involving text can be fascinating to deal with. But there are two main problems to look after. First, deep learning models do not take text data directly as input. Secondly, text can be really messy to deal with when designing deep learning models. But, Keras can help with the preprocessing of text data. […] ...

It is very important to have a good and properly prepared data to execute through a machine learning pipeline. Sometimes you are lucky to get good data from the beginning. But at other times you need to prepare your data before feeding it your machine learning algorithm. In this article, you are going to learn […] ...

The handwritten digits MNIST data set is good enough to get started with image classification, but it is getting old. Therefore, in this article you will be tackling another variant of the MNIST data set, the Fashion MNIST data set. Doing Fashion MNIST classification with Keras can be a lot of fun for those who […] ...

A Support Vector Machine (SVM) is really a powerful Machine Learning Model. It is capable of performing both classification and regression. And Iris flower data set is just perfect for analyzing SVM. So, in this article, we are going to take a peek into the SVM model by using the Iris data set. So, power […] ...