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- Abrar can focus on optimizing the recommendation pipeline for efficiency and speed, ensuring minimal computational overhead.
- Vineeth can assist in fine-tuning the algorithm for faster and more re…
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Такого не должно быть
Сделай utils.py в нём будут все функции (чтения и записи в файл), которые часто ис…
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The project utilizes a combination of data preprocessing techniques, feature extraction methods, and machine
learning algorithms to build a content-based recommendation system for Netflix movies. Exa…
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### Describe the feature
**Enhancement**: Create an advanced case-matching algorithm that connects users with lawyers specializing in specific legal issues.
**Benefit:** Increases relevance and expe…
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In the QA specs we claim that we provide a recommendation for the edit distance algorithm to be used.
For this we have to
* [ ] collect the most popular / widely used algorithms for this task
* [ ] …
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Objective
The primary objective of this project is to develop a book recommendation system that effectively suggests books to users based on their preferences and ratings. By utilizing machine learni…
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Some algorithms are worth being placed into this project. They include,
- [ ] Shortest Path: Dijkstra
- [ ] Backtracking: Eight Queens
- [ ] Data Compression: Huffman
- [ ] Spanning Trees: Krusk…
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**Describe the solution you'd like**
Create a movie recommendation system script in python that learns from my past movie experiences (which i provide to the script or it gets updated with time) and …
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### Problem
Currently in the app you can only sort by your recommendations you've set. But I would like to sometimes just select the one with the lowest kcal and go from there.
### Proposed solut…
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### Pitch
I love the new Follow Suggestions in Mastodon, but they frequently suggest accounts that are obviously dormant. Would it be possible to only suggest 'who to follow' accounts that are active…