🔥 In this video, we are going to build an end-to-end Machine Learning Model - using an unlabelled dataset. We apply the powerful Programmatic Labeling Tool called Snorkel for programmatically creating and managing training datasets for Machine Learning Models. In the Model Training phase, we use CountVectorizer for Feature Representation and Logistic Regression for Classification.

🔥 Programmatic Labeling Series
- Part 1: [ Ссылка ]
- Part 2: [ Ссылка ] [This video]
- Link to Jupyter Notebook: [ Ссылка ]

🔥 Our other popular ML Projects:
1. Sentiment Analysis Project using LSTM: [ Ссылка ]
2. Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask):
---- a. Model Building: [ Ссылка ] (Part-1)
---- b. Model Deployment: [ Ссылка ] (Part-2)
3. Sentiment Analysis Project using Traditional ML: [ Ссылка ]
4. Analytics-enabled Marketing: youtu.be/g7hEPopJ4MY
5. Credit Scoring Project: youtu.be/8jzvzRo3Ij0
6. Face Recognition Project: youtu.be/4EeUkpAYrYo


🔥 Do like, share & subscribe to our channel. Keep in touch:
Email: skillcate@gmail.com
Whatsapp: +91-7404139793
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GitHub: [ Ссылка ]
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