Agenium Scale vectorization library for CPUs and GPUs
content-based movie recommendation system that suggests similar movies using TF-IDF and SBERT embeddings with cosine similarity for efficient matching. Utilized Python, TF-IDF, SBERT, scikit-learn, pandas, and NumPy, enabling fast data processing and improved recommendation accuracy through semantic similarity understanding.
In today’s fast-paced digital landscape, YouTube creators often miss opportunities due to rapid trends and shifting viewer preferences. Identifying what resonates with audiences can be challenging before trends change again. This project was inspired by the need for creators to make informed decisions swiftly.
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