CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View
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Updated
Jun 30, 2022 - Python
CVPR2022 (Oral) - Rethinking Semantic Segmentation: A Prototype View
[ICMLSC 2018] On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset
C++/Python implementation of Nearest Neighbor Descent for efficient approximate nearest neighbor search
MATLAB code for bonferroni-means fuzzy k nearest neighbor classifier (BM-FKNN)
Built prediction and retrieval models for document retrieval, image retrieval, house price prediction, song recommendation, and analyzed sentiments using machine learning algorithms in Python
An MPI based implementation of K-NN search algorithm, aimed for use on CPU clusters.
Use Kmean Clustering and Collaborative filtering approach for the recommendation problem
This is the model that I build to grade future essay based on the that is provided.
How can I trust you? An intuition and tutorial on trust score
1-Bag of SIFT representation and nearest neighbor classifier
Programming Assignment on Data Mining: Movies Review Classification
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms [NeurIPS 2020]
An efficient Nearest Neighbor Classifier for the MINST dataset. It uses a VP Tree data structure for preprocessing, thus improving query time complexity
This is a course project to select a subset of data to build an efficient nearest neighbor classifier. Choosing a representative subset of "prototypes" from the training set is crucial for accelerating nearest neighbor classifiers. This project proposes projecting the data into a latent space using a pretrained embedder.
These are computer assignments of the book "An Introduction to Machine Learning" by Miroslav Kubat
Feature wise normalization: An effective way of normalizing data
As part of the UCSanDiego online course "Machine Learning Fundamentals"
from scratch, KNN implementation and plot
AI to predict whether online shopping customers will complete a purchase
Here I am starting with Machine Learning notes after SQL notes. I have covered the following topics such as:
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