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The focus on the top 10 in vector search is a product of wanting to prove value over keyword search. Keyword search is going to miss some conceptual matches. You can try to work around that with tokenization and complex queries with all variations but it's not easy. Vector search isn't all that new a concept. For example, the annoy library (https://github.com/spotify/annoy), an open source embeddings database. - Source: Hacker News / 8 months ago
If you want to go larger you could still use some simple setup in conjunction with faiss, annoy or hnsw. Source: 10 months ago
I then use annoy to compare them. Annoy can use different measures for distance, like cosine, euclidean and more. Source: 11 months ago
Yes you can do this for equality predicates if your row groups are sorted . This blog post (that I didn't write) might add more color. You can't do this for any kind of text searching. If you need to do this with file based storage I'd recommend using a vector based text search and utilize a ANN index library like Annoy. Source: 11 months ago
If you need large scale (1000+ dimension, millions+ source points, >1000 queries per second) and accept imperfect results / approximate nearest neighbors, then other people have already mentioned some of the best libraries (FAISS, Annoy). Source: 12 months ago
After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: about 1 year ago
Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 1 year ago
MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 2 years ago
Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
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