Data Science Notebook on a Classification Task, using sklearn and Tensorflow.

Tools and recipes to train deep learning models and build services for NLP tasks such as text classification, semantic search ranking and recall fetching, cross-lingual information retrieval, and question answering etc.

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Unofficial implementation for ScanNet (a fast WSI prediction method) in PyTorch.

The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.

Fraud detection using lgb, catboost, rf, etc

Train Image classification on CIFAR10 using tensorflow and keras. Create a inference using opencv. OpenCV to read tensorflow graph.

Continual learning using variational prototype replays

The MAFAT challenge, by the Israeli Department of Defense. Deep Learning based approach to classify radar signatures of humans and animals.

Given a pair of questions on Quora, the NLP task aims to classify whether two given questions are duplicates or not. The underlying idea is to identify whether the pair of questions have the same intent though they might have been structured differently .

It is a binary classification task, where given a set of features we need to predict whether the employee is likely to leave or not

radiomics

ISIC2016challenge

😄 😟 😂 An emotion classification web service 😄 😟 😂

CNNs usage with tensorflow.js, an example for handwritten data and recognition by cnn

A random forest algorithm is implemented in Python from scratch to perform a classification analysis.

Top solution of Janata Hack: Mobility Hack

Comparative Analysis of Basic ML algorithms and its conclusion.

LSTM, Bi-LSTM PyTorch project for Information Retrieval and NLP course at University of New South Wales

Code that exemplifies neural network solutions for classification tasks with DyNet. On top of that, the code demonstrates how to implement a custom classifier that is compatible with scikit-learn's API.