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TOPIC MODELING | LATENT DIRICHLET ALLOCATION ( LDA ) | IN DEPTH | BY YASHVI PATEL
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Topic Models are a type of statistical language models used for finding hidden structures in a collection of texts. For example, when we think of 'entertainment' - the topic, the words that come to the mind are 'movie', 'dance', 'youtube' and so on.
In this video, I am explaining the unsupervised machine learning technique, Latent Dirichlet Allocation (LDA), for automatically finding the mixture of similar words together, thus forming the topic.
If you like these tutorials and would like to support them then the easiest way is to simply like the video and give it a thumbs up & also it's a huge help to share these videos with anyone who you think would find them useful.
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⭐️ ABOUT ME ⭐️
I am Yashvi Patel, Software Developer with Data science skills and Kaggle Notebook Master. I created this channel to share my knowledge and experience with you all. This channel will include practical tutorials solving problems from Kaggle datasets and competitions. I will upload videos related to Data Science, Machine learning, Deep learning, Natural Language Processing, and Computer vision.
In this video, I am explaining the unsupervised machine learning technique, Latent Dirichlet Allocation (LDA), for automatically finding the mixture of similar words together, thus forming the topic.
If you like these tutorials and would like to support them then the easiest way is to simply like the video and give it a thumbs up & also it's a huge help to share these videos with anyone who you think would find them useful.
Please consider clicking the SUBSCRIBE button to be notified for future videos.
⭐️ ABOUT ME ⭐️
I am Yashvi Patel, Software Developer with Data science skills and Kaggle Notebook Master. I created this channel to share my knowledge and experience with you all. This channel will include practical tutorials solving problems from Kaggle datasets and competitions. I will upload videos related to Data Science, Machine learning, Deep learning, Natural Language Processing, and Computer vision.
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