Predictive Maintenance: Predicting Machine Failure from Sensor Data with Python
Build a leakage-safe, reproducible machine-failure classifier and evaluate rare-event performance with appropriate baselines and metrics.
Seaborn
18 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.
Univariate Stock Market Forecasting using Facebook Prophet in Python
This tutorial gives an overview of Facebook Prophet and shows how to use the framework in Python to create a univariate time series forecast.
On-Chain Analytics: Metrics for Analyzing Blockchains in Python
This article combines blockchain data and historic crypto prices from CryptoCompare in a comprehensive on-chain analysis using Python.
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.
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.
Leveraging Distributed Computing for Weather Analytics with PySpark
This tutorial teaches the basics of Big Data analytics with Pyspark, based on the ingestion, processing, and analysis of Zurich weather data.
Stock Market Forecasting Neural Networks for Multi-Output Regression in Python
This tutorial develops and evaluates a Keras multi-output regression model that forecasts ten future Apple trading sessions in one pass.
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
Classifying Reported Crime Categories in San Francisco with Python
Build and evaluate a reproducible multiclass model for historical San Francisco incident categories, including responsible-use limitations.
Color-Coded Cryptocurrency Price Charts in Python
Create color-coded cryptocurrency price charts with Python to visualize the lag between price points and the bitcoin halving.
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
A compact, reproducible sentiment-analysis example using synthetic text data, TF-IDF features, and a comparison of Naive Bayes and Logistic Regression.
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.
Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?
COVID-19 has had a strong impact on the global stock market. We can measure this influence with a stock market correlation matrix in Python.