Name: John Bosco
Type: User
Company: National Institute of Advanced Industrial Science & Technology
Bio: PhD researcher working on Data integration, Entity matching, and Natural language processing.
Location: Tsukuba, Japan
Blog: boscoj2008.github.io
John Bosco's Projects
Learning node representation using edge semantics
data and code for the paper: "Bridging the Gap between Reality and Ideality of Entity Matching: A Revisiting and Benchmark Re-Construction"
AE
datasets for EM
Pytorch library for fast transformer implementations
Google Research
Package for "pruning" weighted complex networks based on the Marginal Likelihood Filter.
hadoopiii2
Hierarchical Attention Networks for document classification
Deep Learning: Image classification, feature visualization and transfer learning with Keras
Sentence embeddings (InferSent) and training code for NLI.
contains files and scripts for training InferSent algorithm
This repository contains the code and data download links to reproduce the experiments of the PVLDB paper "Dual-Objective Fine-Tuning of BERT for Entity Matching" by Ralph Peeters and Christian Bizer.
Code for paper: KNN-BERT: Fine-Tuning Pre-Trained Models with KNN Classifier
Source Code Repository for the IST256 Python course
The solution to the Loan Prediction Practice Problem on Analytics Vidhya (https://datahack.analyticsvidhya.com/contest/practice-problem-loan-prediction-iii/)
Anomaly detection for streaming data using autoencoders
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Natural Language Processing Tutorial for Deep Learning Researchers
Mobile phone reviews from Amazon.com are analysed to find trends and patterns and determine which characteristics are mentioned most by customers and with what sentiment for each product.
Data augmentation for NLP
This repository contains tools to help compile Overleaf documents locally
CNN classifier for recognizing plant diseases using Keras
Plotting temperatures in the New Orleans area for the period 2005-2015 using matplotlib
Repository to store sample python programs for python learning
Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful