There are 0 repository under knearest-neighbors topic.
Knn implementation without K parameter
An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.
C++ implementation for machine learning algorithm K-NN
A simple implementation of K Nearest Neighbors classifier model in python.
A semantic search engine to find questions semantically similar to given query using Elastic Search, Tensorflow, Universal Sentence Encoder, AWS Lambda, API Gateway
Predicting the champion of the 2023 Cricket World Cup through the implementation of the Random Forest algorithm.
Machine learning and Deep learning project
AU331机器学习与知识发现课程项目——拍照矩阵计算器开发
Building a ML model that can predicts the species of the flower from the measurements of the petal and the sepal
Recommendation System Using K-Nearest Neighbors .
This project is an application for classifying the quality of coconuts using the K Nearest Neighbors algorithm. It is built with Streamlit for easy deployment.
n this project I used different regression algorithms to predict flight delay. I used Kaggles free GPUs and Datasets from Zindi in this project. Those different algorithms include random forrest, decision tree, xgboost and so on. Initially I used feature engineering and used data visualization techniques to get my data into the best shape.
Intro to k-nearest neighbors (KNN) with cuML.
DataHipsters is a service implementing MinHash similarity on a Key-Value Database (Google AppEngine/GCloud), including an API for k-nearest neighbors (k-nn) used in Online Recommender Systems.
Machine Learning Hyperparameter Optimization (Grid Search and Random Search)
A swift implementation of a KNearestNeighbour Classifier in swift.
Esse pequeno projeto tem como objetivo fazer testes de acurácia com rede neural com apenas um neurônio sem classificadores e com 2 (dois) classificadores, sendo eles KNN e 1R.
A multiclass classification problem to classify malware classes.
Sklearn, logistic regression, Naive Bayes classifier, K-Nearest Neighbors, decision trees
Self Work Coding Files related to Data Science
Image classification in the gastrointestinal tract with KNN and CNN
In this challenge, we ask you to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).
This model predicts whether the survivors of the Titanic survived or not. In this file, different classification models are compared and predictions are done from the model(s) having highest accuracy. Here, 'training_data.csv' is used for training and testing the models and 'testing data.csv' is used for predictions. These data sets are from Kaggle
Using machine learning algorithms to predict SpaceX Falcon 9's First Stage Landing Sucess
Demonstrating different Machine Learning Model
Compared the metrics and performance of different classification algorithms on Heart Failure dataset from UCI ML Repository
Created a Python program for K Nearest Neighbor Algorithm implementation from scratch. Determined the Euclidean distance between the data points to classify a new data point as per the maximum number of nearest neighbors. Implemented the algorithm on sklearn’s IRIS dataset which achieved an accuracy of 95.56%.
The purpose of this project is to promote understanding -- my own and others' -- of fundamental data science and machine learning concepts and tools. It currently consists of one notebook that classifies fruit types based on weight, volume, and image data.
Using Machine Learning to rank a list of customers most likely to buy a Car Insurance for a cross-sell campaign.
Data Science - K-Nearest Neighbors (KNN) Work
Predicting the results of the given transactions by classification
Flight_Price Prediction using Machine Learning.(Regression Use Case)
In this repository I am gonna show the main and most popular non-supervised clustering algorithms with short explanations.