Handwritten Digit Recognition using Machine Learning and Deep Learning

AUTOMATED TYPE CLASSIFICATION OF GLAUCOMA DETECTION USING DEEP LEARNING

Support Vector Machine in Javascript

Superpixel-based semantic segmentation, with object pose estimation and tracking. Provided as a ROS package.

阅读LibSVM源码的知识整理与思考（已完结）

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 fo…

COVID-19 Question Dataset from the paper "What Are People Asking About COVID-19? A Question Classification Dataset"

Service for machine learning model prediction in Flask, celery

a robust AI library for detecting profanity in russian language (regex/SVM based), библиотека для детекции нецензурных слов в русском языке

Speech_Emotion_detection-SVM,RF,DT,MLP

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…

EKG Analysis code for the MI3 intern group at CHOC Children's

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.

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 datase…

Lecture notes of Professor Stéphane Mallat - Collège de France - Paris

8 Articles and Project Builds to learn Machine Learning Models.

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 ha…

My Implementation of Machine Learning models

Predict whether income exceeds $50K/yr based on census data.

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.