In this article, you will study false positives and false negatives in Machine Learning. Learning Prediction Models These two concepts, i.e., false positives and false negatives, f.... Read More
So, here we’ll be looking at a Python implementation of the logistic regression algorithm. We will be using the dataset available below to implement our algorithm. The datase.... Read More
XGB or XGBoost stands for eXtreme Gradient Boosting. It tries to predict models using a gradient boosting framework. A large number of developers contribute to the XGB open-source..... Read More
Extra Tree Classifier is a type of machine learning algorithm which is closely related to the decision tree algorithm. It collects the result of various decision trees into a fores.... Read More
In this tutorial, we will explore the different types of regularization, their advantages and disadvantages and how to apply them and implement the same in Python. When the number .... Read More
CIFAR-10 dataset is a collection of images used for object recognition and image classification. CIFAR stands for the Canadian Institute for Advanced Research. There are 60,000 ima.... Read More
In this tutorial, we will learn about one of the supervised Machine learning techniques (i.e) K-Nearest Neighbor Algorithm from scratch in Python. It is mainly used for classificat.... Read More
Performance estimation is crucial for any model. Cross-validation method is one of the estimation strategies which improves the accuracy of the model. In this tutorial, you will le.... Read More