#Svm-classifier
Showing 21 of 21 repositories tagged #svm-classifier, ranked by stars
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset
[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection
DDoS attacks detection by using SVM on SDN networks.
A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach
Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks
Football Match prediction using machine learning algorithms in jupyter notebook
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python
AI & Machine Learning: Detection and Classification of Network Traffic Anomalies based on IoT23 Dataset
This repository contains works on a computer vision software pipeline built on top of Python to identify Lanes and vehicles in a video. This project is not part of Udacity SDCND but is based on other free courses and challanges provided by Udacity. It uses Computer vision and Deep Learrning Techniques. Few pipelines have been tried on SeDriCa, IIT Bombay.
Android Malware Detection Using Machine Learning Classifiers ( Using Permissions requested by Apps)
PyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
The (un)official repository for my master thesis
Predicting air pollution level in a specific city
Face detection implementation with different methods and applications
This is a Statistical Learning application which will consist of various Machine Learning algorithms and their implementation in R done by me and their in depth interpretation.Documents and reports related to the below mentioned techniques can be found on my Rpubs profile.
Modular full-stack ML project leveraging Groq API, Streamlit, Supabase, JSON, SciPy, SciKit-Learn, Plotly & EmailJS, alongside libraries - NumPy, Pandas, Utils, OS, Base64, Re, Pillow & DateTime.
Script to extract CNN deep features with different ConvNets, and then use them for an Image Classification task with a SVM classifier with lineal kernel over the following small datasets: Soccer [1], Birds [2], 17flowers [3], ImageNet-6Weapons[4] and ImageNet-7Arthropods[4].
UpGrad Course workout for ML & AI
Adaptive Reinforcement Learning of curious AI basketball agents
A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.