Topic Modeling by Group Using Deep Learning in Python | NLP

Building one general topic model is not enough in some cases, especially when there are different categories with various properties and characteristics. For example, a commercial bank may be interested in topic models built for different lines of products such as credit cards, checking accounts, or student loan. A hotel chain may be interested in the topics in reviews for different locations. In this tutorial, we will talk about how to analyze topics by group using Airbnb data in Python. We will cover: 👉 How to build multiple topic models by category? 👉 How to extract topics by group from one general topic model? ⏰ Timecodes ⏰ 0:00 - Intro 0:48 - Step 1: Install and Import Libraries 1:20 - Step 2: Download And Read Airbnb Review Data 3:22 - Step 3: Remove Noises from Topic Top Words 5:30 - Step 4: Group Data Preprocessing 6:21 - Step 5: Multiple Topic Models by Group 9:56 - Step 6: One Topic Model for Multiple Groups ❤️ Blog post with code for this video: @AmyGrabNGoInfo/topic-modeling-by-group-using-deep-learning-in-python-5685701914df 📒 Code Notebook: 🙏 Give me a tip to show your appreciation and help me keep providing free content: ✅ Join Medium Membership: If you are not a Medium member and want to support me to keep providing free content (😄 Buy me a cup of coffee ☕), join Medium membership through this link: @AmyGrabNGoInfo/membership You will get full access to posts on Medium for $5 per month, and I will receive a portion of it. Thank you for your support! 🎞️ NLP playlist: 📺 Videos mentioned in the video Google Colab Tutorial for Beginners: Topic Modeling with Deep Learning Using Python BERTopic: Hyperparameter Tuning for BERTopic Model in Python: 🔥 Check out more machine learning tutorials on my website! 🛎️ SUBSCRIBE to GrabNGoInfo 📧 CONTACT me at contact@ #topicmodel #NLP #MachineLearning #DataScience #GrabNGoInfo