Mathematics is one of the prerequisites that most data science enthusiasts fear to get into machine learning. Without learning math, it will be very difficult for you to create your algorithms although it is possible to learn machine learning if…
There are so many applications in your smartphone that uses machine learning somewhere to provide a better user experience. Social Media applications are such applications that are found in every smartphone. So to understand the use of machine learning nothing…
Passive Aggressive Regression belongs to the category of online learning in machine learning. It is not one of the most commonly used machine learning algorithms, but it can nonetheless be used to achieve efficient results that solve regression-based problems. So,…
Whenever we are looking for hotels for vacation or travel, we always prefer a hotel known for its services. The best way to find out whether a hotel is right for you or not is to find out what people…
In machine learning, accuracy is one of the most important performance evaluation metrics for a classification model. The mathematical formula for calculating the accuracy of a machine learning model is 1 – (Number of misclassified samples / Total number of…
Fake news is one of the biggest problems with online social media and even some news sites. Most of the time, we see a lot of fake news about politics. So using machine learning for fake news detection is a…
Stochastic gradient descent is a machine learning algorithm that is used to minimize a cost function by iterating a weight update based on the gradients. If you’ve never used the SGD classification algorithm before, this article is for you. In…
Detecting spam alerts in emails and messages is one of the main applications that every big tech company tries to improve for its customers. Apple’s official messaging app and Google’s Gmail are great examples of such applications where spam detection…
One of the common tasks in natural language processing is sentiment analysis. If you want to work on a project based on natural language processing, sentiment analysis will be a good choice. Before you start a project on sentiment analysis,…
In machine learning, variance is the difference between the actual samples of the dataset and the predictions made by the model. When working on a regression-based machine learning problem, it is very useful to know how much of the variance…