Super fast K-Means for High-Dimensional vectors on CPUs (x86, ARM) and GPUs — for Python and C++. Up to 10x faster clustering of embeddings than FAISS and Scikit-Learn
search osu maps by mapping style
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization
Implementation of various machine learning algorithms from scratch, including Linear Regression, K-Nearest Neighbors, Decision Trees, and K-Means clustering. Also done EDA on data, Implemented LSH, IVF, SLIC algorithms also with evaluation metrics
A semantic search indexing system designed to efficiently retrieve top matching results from a database of 20 million documents. Given the embedding of a search query, it quickly identifies and returns the most relevant documents
A web application for predicting the chance of an IVF/ICSI cycle yielding a D5 embryo suitable for transfer or freezing.
A tiny approximate K-Nearest Neighbour library in Python based on Fast Product Quantization and IVF
The IVF Hypernatremia Calculator is a tool that assists medical professionals in calculating the appropriate amount of flushing or fluids for IVF patients by simply entering the patient's age, gender, weight, sensible losses and insensible losses. It helps ensure accurate calculations and avoid hypernatremia.
A machine learning system for identification of ovarian response and deployment of ovarian stimulation strategies in ART
Meta-analysis of DNA methylation in ART
visualization tool for vector search index
Predicting the probability of an IVF patient having an embryo suitable for D5 transfer or freezing.
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