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.
#Supervised Learning
17 tutorials
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.
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
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
Forecasting Beer Sales with ARIMA in Python
This Python tutorial shows how to use Auto-ARIMA for time series forecasting using the example of forecasting beer sales.
Image Classification with Convolutional Neural Networks - Classifying Cats and Dogs in Python
Learn about image classification with deep learning and develop a convolutional neural network that distinguishes between cats and dogs!
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.
Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques
Feature engineering for multivariate time series models using the example of stock market forecasting with Python and Keras Neural Networks.
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.
Stock Market Prediction using Multivariate Time Series and Recurrent Neural Networks in Python
This tutorial shows how to model a multivariate time series using a recurrent neural network to forecast the stock market.
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.
Measuring Regression Errors with Python
This tutorial presents six regression error metrics to measure model performance and shows how to implement them with Python and Scikit-learn
Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python
This article shows how to create a rolling multi-step forecast for a rising sine curve using Keras neural networks with lstm layers in Python
Stock Market Prediction using Univariate Recurrent Neural Networks (RNN) with Python
This article shows how to train a univariate neural network model for stock market forecasting with Python and Scikit-learn.
Flight Delay Prediction using Azure Machine Learning
Want to learn about flight delay prediction? This tutorial develops a classifier in Azure Machine Learning that predicts flight delays.