shamimtowhid Goto Github PK
Name: Md Shamim Towhid
Type: User
Company: University of Regina
Bio: “ Code is like humor. When you have to explain it, it’s bad.” – Cory House
Location: Regina, SK, Canada
Name: Md Shamim Towhid
Type: User
Company: University of Regina
Bio: “ Code is like humor. When you have to explain it, it’s bad.” – Cory House
Location: Regina, SK, Canada
Repository for 5G-Monarch paper
This repository is an initiative to automate the deployment process of 5G core network in cloud environment.
This is a dataset of 5G network traffic for use with machine learning tools to benchmark attack detection capabilities for multiple different models. The dataset contains simulated normal and attack 5G network traffic.
This is the code of CML-IDS
This repo contains an implementation of a very popular algorithm used in deep Reinforcement Learning named DDPG (Deep Deterministic Policy Gradient). This project is done as a part of Udacity's Deep Reinforcement Learning nanodegree program. In this project, I tried to solve a Unity ML agent environment named Reacher with DDPG algorithm.
10 Weeks, 20 Lessons, Data Science for All!
the objectives of this experiment is to know how a simple classifier works. The classifier implemented in this experiment may not work correctly in all situation but the purpose to know how a classifier works can be accomplished. Firstly in the introduction section we will discuss the basic things of a classifier and also we will know what includes in our experiment. Then we will go for the implementation of our experiment. We will use MATLAB tools to implement our classifier. After that we will perform a simple result analysis on the result. Then we will conclude our experiment.
This project aims to detect intrusion in an SDN network as early as possible.
This repository describes the demonstration of encrypted network traffic classification in SDN environment. A testbed is created using Mininet in this project. A RYU controller application is developed to classify network traffic in real-time.
Draft of the fastai book
Public resources for classes, tutorials, and demonstrations.
Open source 5G core network base on 3GPP R15
In this project I tried to implement FTP protocol using socket programming in JAVA.
GTP-U Linux Kernel Module
the objective of this experiment is to understand one of the very popular clustering algorithm known as K-Means clustering algorithm. This is an unsupervised learning method which means the class label is unknown here. But to measure the performance of the algorithm we need to know the ground truth. Here in this experiment we will use cluster purity as performance measure of the classifier. Here we use the dataset that has 150 data with four dimension each. We will cluster the whole dataset into three cluster here, so in our experiment k=3.
the objective of this experiment is to classify some sample points using the posterior probabilities which uses Gaussian distribution to calculate the likelihood probabilities. The objective of this type of classifier is to minimize the error rate during classification. So this classifier takes decision based on the most posterior probabilities. This classifier is also known as Bayes classifier with minimum error.
the objective of this experiment is to apply perceptron algorithm to find the weights of a linear discriminant function. Perceptron algorithm is an incremental way for finding the weights of a linear discriminant function. In this experiment we will apply this algorithm to find weights of a given linear discriminant function. In this algorithm we start with a random weights and gradually we will forward to the actual weights. Though this algorithm has some drawbacks we will apply it for its simplicity. There are two implementation of this algorithm: one is batch processing (also known as many at a time), and the other is one at a time. We will evaluate our sample data with both process and in the result analysis section we will compare the performance of this two methods with different learning rate.
This project aims to develop network-based intrusion detection system using ML models. We use data plane programming to collect features and deploy our ML model in the data plane insteaded of control plane.
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
https://huyenchip.com/ml-interviews-book/
Compilation of P4 exercises, examples, documentation, slides for learning or teaching
P4 language tutorials
This project aims to develop a visualization tool that is useful to identify network congestion.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.