Arijit Nandi's Projects
Applied Deep Learning Course
Ensemble learning related books, papers, videos, and toolboxes
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
Data structures & algorithms cheat sheet
CNN using Numpy (Used Keras for Cifar-10 dataset.)
Acceptance rates for the major AI conferences
Scalable data collection from multiple sensors (IMU, infrared camera, EMG, EEG, GSR, HRM, environmental sensors, eye tracker).
Emotion Recognition, EEG Mapping, Azimuthal Projection Technique, CNN
This notebook is part of my blogpost, in which we'll make a deep neural network from scratch in plain Numpy
Jonah Lawrence's Profile README
A Docker-Based Federated Learning Framework Design and Deployment for Multi-modal Data Stream Classification
Dynamic Q-Learning Based Feature Selection approach
A Federated Learning based Android Malware Classification System
A Python module for use with Elsevier's APIs: Scopus, ScienceDirect, others.
Accuracy Improvement of Neural Network Training using Particle Swarm Optimization and its Stability Analysis for Classification
Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.
A Federated Learning Method for Real-time Emotion State Classification from Multi-modal Streaming
Federated Learning with Exponentially Weighted Moving Average for Real-Time Emotion Classification
Federated Learning Framework is an open-source framework for Machine Learning that is dedicated to data privacy
This project is created to understand the multicollinearity with VIF scores and how to fix it with code in python
This is a repository for the open-source project flaskriver which will make it easier to combine the lightweight web-framework flask with the online-ML library river.
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
README for my Github Profile
Explaining Git and GitHub.
Glaucoma and Non-Glaucoma classification using ML/Dl and ensemble approaches using Image Feature Extraction Using HOG (Histogram of Gradient)
In this paper, we developed a machine learning model ensemble approach consisting of a support vector machine (SVM), random forest (RF), Multilayer Perceptron (MLP), and Majority-VotingEnsemble classifiers.