Predictive Maintenance: Predicting Machine Failure using Sensor Data with XGBoost and Python
By using machine learning and Python, businesses can predict equipment failures before they happen and optimize their maintenance cycles.
Scikit-Learn
14 tutorials
How to Use Hierarchical Clustering For Customer Segmentation in Python
In this tutorial, we will use Python and the scikit-learn library to apply hierarchical clustering to a dataset of customer data.
Feature Engineering and Selection for Regression Models with Python and Scikit-learn
This guide provides tips on feature exploration, engineering, and selection for machine learning using Python and Scikit-Learn
Create a Personalized Movie Recommendation Engine using Content-based Filtering in Python
This article shows how to employ a bag of words model and cosine similarities to create a content-based movie recommender with Python.
Unveiling Hidden Patterns in the Cryptocurrency Market with Affinity Propagation and Python
This tutorial shows how to use affinity propagation to analyze asset clusters in the crypto market using Python.
Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python
Learn how to use Random Search to tune the model hyperparameters of a Random Forest with Python that predicts house sale prices.
Stock Market Forecasting Neural Networks for Multi-Output Regression in Python
This tutorial develops a multi-output regression model in Python that generates a multi-day stock market forecast for the S&P500
Cluster Analysis with k-Means in Python
This tutorial presents k-mean clustering and how to perform a cluster analysis on synthetic data with Python and Scikit-Learn.
Multivariate Anomaly Detection on Time-Series Data in Python: Using Isolation Forests to Detect Credit Card Fraud
This article describes multivariate anomaly detection in the example of credit card fraud using Random Isolation Forests in Python
Predictive Policing: Preventing Crime in San Francisco using XGBoost and Python
This article predicts crime types in San Francisco with the XGboost classifier in Python and displays them on a crime map of SF
Customer Churn Prediction - Understanding Models with Feature Permutation Importance using Python
This tutorial shows how to build a customer churn prediction model in telecommunications. We will use Python and measure feature importance.
Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python
Learn how to tune the model hyperparameters of a Random Forest that predicts the survival of Titanic passengers using grid search in Python.
Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python
This article deals with sentiment analysis and shows how to build a sentiment classifier using logistic regression and naive Bayes in Python.
Classifying Purchase Intention of Online Shoppers with Python
Learn to use logistic regression to solve two-class prediction problems in Python by classifying online shoppers' purchase intentions.