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# Semi-Supervised Learning. How to overcome the lack of labels


- **Date:** Friday, Jul 19, 2024
- **Time:** 14:20–14:50 (30 min)
- **Room:** STAGE 11 (700)
- **Event:** World Congress 2024

## Recording

[Watch recording](https://www.wearedevelopers.com/videos/933-semi-supervised-learning-how-to-overcome-the-lack-of-labels)

## Description

Semi-supervised learning, an innovative approach in machine learning, strategically positions itself between the realms of supervised and unsupervised learning. This methodology uniquely utilizes a combination of a small portion of labeled data and a substantially larger set of unlabeled data for model training. Its significant advantage lies in scenarios where gathering a fully labeled dataset is prohibitively costly or logistically unfeasible. By blending the directive nature of labeled data with the extensive insights of unlabeled data, semi-supervised learning offers a practical, cost-effective solution for comprehensive model training, especially in data-scarce environments.

## Speaker

### [Alex Timashov](https://www.wearedevelopers.com/@alex-timashov)

ML Engineer at Meta


## Related talks at this congress

- [Machine learning 101: Where to begin?](https://www.wearedevelopers.com/events/world-congress-2024/sessions/55-machine-learning-101) — Lutske van der Meer
- [Unlocking the Power of AI: Accessible Language Model Tuning for All](https://www.wearedevelopers.com/events/world-congress-2024/sessions/106-unlocking-the-power) — Cedric Clyburn, @technicallylegare
- [Make it simple, using generative AI to accelerate learning](https://www.wearedevelopers.com/events/world-congress-2024/sessions/276-make-it-simple-using) — Duan Lightfoot
- [Large Language Models  ❤️ Knowledge Graphs](https://www.wearedevelopers.com/events/world-congress-2024/sessions/122-large-language) — Michael Hunger