svm-model
There are 450 repositories under svm-model topic.
anujdutt9/Handwritten-Digit-Recognition-using-Deep-Learning
Handwritten Digit Recognition using Machine Learning and Deep Learning
shakiliitju/Credit-Card-Fraud-Detection-Using-Machine-Learning
Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent transactions. Credit card fraud refers to the physical loss of a credit card or the loss of sensitive credit card information.
kr-viku/GLAUCOMA-DETECTION
AUTOMATED TYPE CLASSIFICATION OF GLAUCOMA DETECTION USING DEEP LEARNING
mljs/svm
Support Vector Machine in Javascript
jhu-lcsr/sp_segmenter
Superpixel-based semantic segmentation, with object pose estimation and tracking. Provided as a ROS package.
bbd03/check-swear
a robust AI library for detecting profanity in russian language (regex/SVM based), библиотека для детекции нецензурных слов в русском языке
WeltXing/libsvm-sc-reading
阅读LibSVM源码的知识整理与思考（已完结）
jecampagne/cours_mallat_cdf
Lecture notes of Professor Stéphane Mallat - Collège de France - Paris
praweshd/speech_emotion_recognition
In this project, the performance of speech emotion recognition is compared between two methods (SVM vs Bi-LSTM RNN).Conventional classifiers that uses machine learning algorithms has been used for decades in recognizing emotions from speech. However, in recent years, deep learning methods have taken the center stage and have gained popularity for their ability to perform well without any input hand-crafted features. Speech emotion on sets obtained from RAVDESS corpus is classified using a conventionally used Support Vector Machine (SVM) and its performance is compared to that of a bidirectional long short-term memory (LSTM).
SinghAbhi1998/Stock-Market-Price-Prediction
Stock Market Price Prediction: Used machine learning algorithms such as Linear Regression, Logistics Regression, Naive Bayes, K Nearest Neighbor, Support Vector Machine, Decision Tree, and Random Forest to identify which algorithm gives better results. Used Neural Networks such as Auto ARIMA, Prophet(Time-Series), and LSTM(Long Term-Short Memory) then compare make Inferences about the model.
IsmoilovMuhriddin/IRIS-data-model-service
Service for machine learning model prediction in Flask, celery
JerryWeiAI/COVID-Q
COVID-19 Question Dataset from the paper "What Are People Asking About COVID-19? A Question Classification Dataset"
blhprasanna99/speech_emotion_detection
Speech_Emotion_detection-SVM,RF,DT,MLP
samyachour/EKG_Analysis
EKG Analysis code for the MI3 intern group at CHOC Children's
Goutam1511/Sign-Language-Recognition-using-Scikit-Learn-and-CNN
The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).
Wb-az/timeseries-sensor-anomaly-detection
Unsupervised anomaly detection in vibration signal using PyCaret vs BiLSTM
RyanRana/The-Simplest-Guide-to-Machine-Learning-Models.
8 Articles and Project Builds to learn Machine Learning Models.
emirhanai/Classification-thanks-to-the-SVM-model-with-7-years-of-ozone-data-with-Machine-Learning
I developed 2 machine learning software that predict and classify ozone day and non-ozone day. The working principle of the two is similar but there are differences. I got the dataset from ics.icu. Each software has a different mathematical model, Gaussian RBF and Linear Kernel, and classifications are visualized in different ways. I would be happy to present the software to you!
amazingcoderpro/flight-delay-prediction
2018年全球程序员大赛参赛作品, 在给定的数据基础上,加上自己采集的飞机、天气等影响因子, 利用svm算法预测航班延误率.
ditsme/Machine-Learning
My Implementation of Machine Learning models
agomolka/AdultIncomeAnalysis
Predict whether income exceeds $50K/yr based on census data.
desiFish/Book-Genre-Prediction
The aim of this project is to apply the principles of text mining on a piece of literary text, and categorize it into the genre into which it best fits.
CatalystsReachOut/Diabetes-Prediction-Using-SVM
In this case, we train our model with several medical informations such as the blood glucose level, insulin level of patients along with whether the person has diabetes or not so this act as labels whether that person is diabetic or non-diabetic so this will be label for this case.
javascript-machine-learning/svm-spam-classifier-javascript
🍃 Spam Classifier with Data Preparation and Support Vector Machine (SVM)
coderhersh/Credit-Card-Fraud-Detection
This is a machine learning project made on Credit Card Fraud Detection. The data is taken from Kaggle. Different classification machine learning algorithms have been applied to get the maximum accuracy.
Hulkido/Fisheriris_MATLAB
Fisheriris dataset classifier in Matlab
JrobT/PyFaceProject
An undergraduate project to evaluate classifiers for facial expression recognition.
rajatbansal01/Machine_Learning-and-Data_Analysis
This repository contains various machine problems with solutions with various algorithms.
Ajayay/SVM_on_AFFR
For conceptual understanding you can refer my medium blog which will provide you in-depth knowledge of SVC along with various other factors required in data science.
nbfigueroa/SVMGrad
Matlab/C++ library to evaluate SVM decision function and its derivatives.
Shubhamkumar-op/Disease_prediction
A disease predictive system using machine learning can mainly for diabetes and heart disease related make existing healthcare tasks easier, safer, and more effective by providing accurate predictions and personalized recommendations based on individual health data
sruti-jain/Machine-Learning---Matlab
This repository contains projects from Andrew NG's Machine Learning course at Coursera
ashcode028/Music-Genre-Classification
Classifying audio files using ML algorithms.
MelikaaS/Rain_Prediction_In_Au
I'm going to practice classification algorithms sch as Logistic Regression, KNN, DecisionTree, SVM to create a model based on training data set and evaluate testing data using evaluation metrics such as 'Acuuracy Score', 'Jaccard Index', 'F1_Score', 'LogLoss', 'Mean Absolute Error', 'Mean Squared Error' and 'R2-Score'
prathamesh693/Customer-Churn-Prediction-in-Telecom-Industry
🔍 Predict customer churn in the telecom industry using machine learning models like Decision Tree, XGBoost, and SVM. Includes data preprocessing, model training, evaluation, and a FastAPI app for interactive predictions.
ThanhNg224/Scrape-Classify
Collected 60,000 Vietnamnet articles, preprocessed the data, and trained a scikit-learn model with over 91% accuracy for article classification.