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  • About

relataly.com

  • AI
    • Simple Regression
    • Classification: Two Class
    • Classification: Multi-Class
    • Clustering
    • Time Series Forecasting
    • Anomaly Detection
    • Natural Language
    • Recommender Systems
    • Reinforcement Learning
    • Responsible AI
  • Use Cases
    • Stock Market Forecasting
    • Algorithmic Trading
    • Sentiment Analysis
    • Churn Prediction
    • Fraud Detection
    • Predictive Maintenance
    • Marketing Automation
    • Customer Segmentation
    • Sales Forecasting
    • ChatBots
    • Fighting Crime
    • Risk Management
    • Image Recognition
  • Algorithms
    • CNNs
    • RNNs (LSTM)
    • Decision Trees
    • Random Decision Forests
    • Random Isolation Forest
    • Local Outlier Factor
    • Gradient Boosting
    • Collaborative Filtering
    • Content-based Filtering
    • K-Nearest Neighbors
    • K-Means
    • Affinity Propagation
    • Agglomerative Clustering
    • Logistic Regression
    • Naive Bayes
    • ARIMA
  • Data Science
    • Exploratory Data Analysis
    • Feature Engineering
    • Hyperparameter Tuning
    • Dimensionality Reduction
    • Model Interpretation
    • Data Visualization
    • Correlation
    • Measuring Performance
    • Cross-Validation
    • Vector Databases
    • SQLite
    • Data Science Environments
      • Anaconda
      • Azure Machine Learning
    • Python Libraries
      • Scikit-Learn
      • Tensorflow
      • Keras
      • Pytorch
      • PySpark
      • Chainer
      • OpenAI Gym
      • Seaborn
      • Fairlearn
      • Facebook Prophet
      • GeoPandas
  • Data & APIs
    • OpenAI API
    • REST APIs
    • NewsAPI
    • Coinmarketcap API
    • Coinbase API
    • Gate.io API
    • Yahoo Finance API
    • Statworx COVID-19 API
    • Twitter API
    • Reddit API
    • Kaggle Competitions
    • Synthetic Data
  • About
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  • Telecom.
  • Manufacturing
  • Retail
  • Logistics

Retail

Here you’ll find everything about machine learning use cases in the retail industry.

There are many potential machine learning use cases in the retail industry, such as:

  • Product recommendation: using collaborative filtering or content-based algorithms to recommend products to customers based on their past purchases or browsing behavior
  • Fraud detection: using supervised machine learning algorithms to identify and flag potential cases of fraud, such as fraudulent transactions or fake user accounts
  • Customer segmentation: Retail companies can use unsupervised learning algorithms to group customers into clusters or segments based on their characteristics, such as their purchase history or demographics
  • Sentiment analysis: using natural language processing (NLP) algorithms to analyze customer reviews and feedback and to identify the overall sentiment towards products or the company
  • Personalized pricing: using reinforcement learning algorithms to optimize prices for individual customers based on factors such as their purchase history and market conditions.

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Content-based recommender systems are a popular type of machine learning algorithm that recommends relevant articles based on what a user … Read more

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Build a High-Performing Movie Recommender System using Collaborative Filtering in Python

May 27, 2023May 31, 2021

The digital age presents us with an unmanageable number of decisions and even more options. Which series to watch today? … Read more

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Time series analysis and forecasting is a tough nut to crack, but the ARIMA model has been cracking it for … Read more

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Customer Churn Prediction – Understanding Models with Feature Permutation Importance using Python

May 27, 2023August 2, 2020

Customer retention is a prime objective for service companies, and understanding the patterns that lead to customer churn can be … Read more

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Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python

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Are you ready to learn about the exciting world of social media sentiment analysis using Python? In this article, we’ll … Read more

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Classifying Purchase Intention of Online Shoppers with Python

May 27, 2023May 11, 2020

Online shopping has become a part of our daily lives, and online stores are continually seeking to improve their sales. … Read more

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