DNA Sequencing with Machine Learning in Python – Human DNA dataset
(End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict Bank Customer Churn using Decision Tree with Monte Carlo Cross Validation in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict Bank Customer Churn using Decision Tree with Monte Carlo Cross …
(End-to-End Jupyter Notebook for Citizen Data Scientist & Business Analyst) Write a program to predict Bank Customer Churn using Decision Tree with Grid Search Cross Validation in Python. In this end-to-end applied machine learning and data science notebook, the reader will learn: How to predict Bank Customer Churn using Decision Tree with Grid Search Cross …
Machine learning is a method of teaching computers to learn from data without being explicitly programmed. One of the most commonly used algorithms for classification tasks is the Linear Discriminant Analysis (LDA) algorithm. In this article, we will be discussing how to use LDA for classification in R using the IRIS dataset from …
Decision trees are a popular machine learning algorithm that can be used for both classification and regression problems. They are widely used in data science and are particularly useful for tasks where the goal is to understand the relationships between different variables in a dataset. Decision trees are also easy to interpret and can …
Machine Learning and Data Science in Python using XGBoost with Ames Housing Dataset | Pandas | MySQL
Machine learning and data science are two areas of computer science that are used to analyze, understand, and make predictions about data. One of the most popular techniques for machine learning and data science is XGBoost (eXtreme Gradient Boosting). XGBoost is a type of ensemble method that combines multiple decision trees to make predictions …
Beginner’s Project on Regression in Python Machine learning regression is a type of machine learning where the goal is to predict a continuous value, such as a price or an age, based on a set of input features. It is used to model the relationship between a dependent variable and one or more independent variables. …
Beginner’s Project on Multi-Class Classification in Python Multi-class classification is a type of machine learning problem where the goal is to classify instances into one of multiple classes. This is different from binary classification, where the goal is to classify instances into one of two classes. There are several algorithms that can be used for …
IRIS Flower Classification using Logistic Regression Classifier IRIS flower classification is a common problem in machine learning. The IRIS dataset is a well-known dataset that contains information about different types of IRIS flowers, including their sepal length, sepal width, petal length, and petal width. The goal of IRIS flower classification is to use this …