Bayesian Linear Regression in Python
Machine learning is heavily dependent on statistics for several tasks. There are two approaches to statistics in machine learning, the Bayesian approach and Frequentist approach. Both of these approaches are…
Mastering Multilayer Perceptron Classifier in Python
Multilayer Perceptron (MLP) classifier is an important and powerful neural network model that has been used in machine learning for the classification of data and solving complex problems. It is…
Introduction to Machine learning and its types
A subset of artificial intelligence (AI) is machine learning (ML) enables computers to "self-learn" from training data and get better over time without having to be specifically programmed. Detecting patterns…
Explaining the concepts of dimensionality reduction
Dimensionality reduction is a technique that is used for reducing the number of input variables present in the dataset. This is done to ease the task of modeling as the…
8 ways to handle Imbalance data in Python
Hello everybody, I hope everything is going well. We will talk about 8 ways to handle Imbalance data in Python in this blog post and how it impacts the outcome…
How to detect and remove outliers in Python
Outliers are one of the key parts of a dataset that must be removed during cleaning and pre-processing by using feature engineering approaches. Let us understand what outliers is; these…
Machine learning explained in a simple way
Introduction Machine learning is a form of artificial intelligence that helps us build software applications that can make accurate predictions. Without explicitly programming the models, the machine learning algorithms use…
Top 10 evaluation metrics for classification models
Sam has built a classification model to predict whether the person has a heart attack or not. Now he wants to evaluate the performance of his model. There are a…
