Vector Databases: The Rising Star in Generative AI Infrastructure
How vector databases are transforming AI applications and LLMs by enabling efficient handling of unstructured data and fast similarity search.
Machine Learning
17 tutorials
ChatGPT Prompt Engineering Guide: Practical Advice for Business Use Cases
Discover typical challenges and learn how to engineer prompts for the successful use of ChatGPT in a business context.
Foundation Models Are Here: How Will They Impact Traditional Machine Learning?
Just a year ago, ChatGPT was launched, and it has since catalyzed a seismic shift in the AI landscape. Given the astonishing capabilities of generative AI…
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.
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.
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.
How to Measure the Performance of a Machine Learning Classifier with Python and Scikit-Learn?
Using confusion matrix and error metrics for measuring classification performance in machine learning with 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.
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.
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.