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.

Building a Virtual AI Assistant (aka Copilot) for Your Software Application: Harnessing the Power of LLMs like ChatGPT

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Welcome to the dawn of a new era in digital interaction! With the advent of Generative AI, we’re witnessing a remarkable revolution that’s changing the very nature of how we interact with software and digital services. This change is monumental. Leading the charge are the latest generation of AI-powered virtual assistants, aka “AI copilots”. Unlike … Read more

Building “Chat with your Data” Apps using Embeddings, ChatGPT, and Cosmos DB for Mongo DB vCore

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Artificial Intelligence (AI), in particular, the advent of OpenAI’s ChatGPT, has revolutionized how we interact with technology. Chatbots powered by this advanced language model can engage users in intricate, natural language conversations, marking a significant shift in AI capabilities. However, one thing that ChatGPT isn’t designed for is integrating personalized or proprietary knowledge – it’s … Read more

Using LLMs (OpenAI’s ChatGPT) to Streamline Digital Experiences

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In the age of information overload, finding what you need quickly and efficiently is more important than ever. OpenAI’s GPT technology has the potential to reduce friction between products and services, making it easier for individuals and businesses to find what they need. In this article, we’ll explore some specific examples of how OpenAI is … Read more

9 Business Use Cases of OpenAI’s ChatGPT

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You haven’t had enough of the recent hype about OpenAI? Fantastic! Let’s explore the business use cases for ChatGPT and other Large Language Models (LLMs). ChatGPT is often considered the beginning of a new era of AI adoption. A growing number of ChatGPT users are now using AI in their personal workflows. However, adoption in … Read more

Create a Personalized Movie Recommendation Engine using Content-based Filtering in Python

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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 has previously consumed or liked. This approach aims to identify items with certain keywords, understand what the customer likes, and then identify other items that are similar to items the user has previously consumed or … Read more

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

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The digital age presents us with an unmanageable number of decisions and even more options. Which series to watch today? What song to listen to next? Nowadays, the internet and its vast content offer too many choices. But there is hope – recommender systems are here to solve this problem and support our decision-making. They … Read more

Forecasting Beer Sales with ARIMA in Python

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Time series analysis and forecasting is a tough nut to crack, but the ARIMA model has been cracking it for decades. ARIMA, short for “Auto-Regressive Integrated Moving Average,” is a powerful statistical modeling technique for time series analysis. It’s particularly effective when the time series you’re analyzing follows a clear pattern, like seasonal changes in … Read more

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

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Customer retention is a prime objective for service companies, and understanding the patterns that lead to customer churn can be the key to maintaining long-lasting client relationships. Businesses incur significant costs when customers discontinue their services, hence it’s vital to identify potential churn risks and take preemptive actions to retain these customers. Machine Learning models … Read more

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 dive into how companies are leveraging machine learning to extract insights from Twitter comments, and how you can do the same. By comparing two popular classification models – Naive Bayes and Logistic Regression – we’ll … Read more

Classifying Purchase Intention of Online Shoppers with Python

Customer Purchase Intention Prediction Python Machine Learning

Online shopping has become a part of our daily lives, and online stores are continually seeking to improve their sales. One way to achieve this is by using machine learning to predict customers’ purchase intentions. This innovative process can help businesses understand their customers’ behavior and tailor their marketing strategies accordingly. In this article, we … Read more