[CADL'22, ECCVW] Official repository of paper titled "EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications".

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

Hybrid model of Gradient Boosting Trees and Logistic Regression (GBDT+LR) on Spark

The main aim of the project is to develop a sentiment analyzer that can be used on twitter data to classify it as positive or negative. Our project takes care of the challenge of bilingual comments, where people tweet in two languages, in this case Hindi and English, in the Latin Alphabet.

MedViT: A Robust Vision Transformer for Generalized Medical Image Classification (Computers in Biology and Medicine 2023)

Image classification using XGBOOST by extracting features using VGG16 ImageNet. This project explains the process of using XGBOOST for image classification using pre-trained weights (VGG16) as feature extractors.

Analyzing and Predicting The COVID-19 Global Cases As Well As On The Basis Of Every Possible Individual Country Using Tensorflow and Python

We use our VDEmodel. Our purpose is that predict the distance between car based on Deep-Learning.

A Hybrid Model for Role-related User Classification on Twitter

Django React Boilerplate Template - Hybrid Model, with Session authentication and CSRF Protection

Detecting depressed Patient based on Speech Activity, Pauses in Speech and Using Deep learning Approach

An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound

Here I am combining best of the both worlds, one is traditional Machine Learning and Deep Learning to create a hybrid model which classifies Tomato Leaf Diseases.

A Hybrid Neural Network Approach for Increasing the Absolute Accuracy of Industrial Robots

📖 mmCIF support for hybrid/integrative models

A Machine Learning based predictor to predict the language tag for a question posted on Stackoverflow. It is a Single label classification.

sbml2hyb is a tool for SBML compatible hybrid modelling of biological systems

https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

Building the best machine learning model to detect phishing websites.

Detection of brain cancer is a tedious and very crucial job. Usage of image based clustering can provide a efficient and unsupervised method of brain cancer detection. Due to the nature of image data, direct clustering is highly impossible and inefficient. To overcome the above limitation, hybrid learning methods are adopted. Efficient utilisati…