As aspiring data scientists, we often take labeled data for granted. Those of you who are working in the industry or academia would know how hard it is to get labeled data for your specific Machine Learning problem. In fact, there are hundreds of startups in the market today that provide data labeling services and actually charge you for it.

So, the big question really is: How do I get labeled data for my next big Machine Learning Project?
- Do I manually annotate it, which might take a lifetime? Or,
- Do I hire a data labeling company, which might put a hole in my pocket?
- Well, there is indeed a third option available, called: Programmatic Labeling

Programmatic Labeling is: immensely scalable, and is absolutely free of cost.

🔥 Programmatic Labeling Series
- Part 1: [ Ссылка ] [This video]
- Part 2: [ Ссылка ]
- 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


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