Deepak John Reji's repositories
Clustering-with-Bert-Embeddings
This Tutorial details on how to do clustering using embeddings
Drought-Prediction
Calculating SPI values using Precipitation data
Question_Answering_for_ALL
This tool tries answering data related to any query if the information is available in Wikipedia. The data is dynamically created once the query is passed and the QnA module answers from it. The data is ranked and prioritized based on the query. Images and Youtube videos are fetched with the help of a couple of packages. Finally, a summary will be created and auto-downloaded for the reference.
Text_match
Text similarity check using Fuzzywuzzy package
github-add-youtube-video
A Greasemonkey script to better integrate Youtube videos in Github markdown (pull requests, issues, comments, ...).
Text-Classification-App
This App is a full fledge tool box for any user to train, test and predict a classification model
Topic-Extraction
Extraction of important topics/key phrases from a paragraphs.
Semantic-Search-using-Elmo
This notebook details how to extract sentences for a search query using the power of Elmo
ailab
Experience, Learn and Code the latest breakthrough innovations with Microsoft AI
Classification-Model-Tensorflow-Embedding-Projector
This Tutorial explains the steps to train a classification model using a Deep Learning Architecture and project the embeddings in Tensorflow Projector
color-names
Provides color names and HTML/RGB mappings in various output formats.
dataset-sts
Semantic Text Similarity Dataset Hub
Entity-Extraction
Rule Based Approaches
FineTune-DistilBERT
Huggingface transformers: Finetuning DistilBERT on a toxic comment binary classification task.
flask-share
Create social share component in Jinja2 template based on share.js.
KeyBERT
Minimal keyword extraction with BERT
SimpleHTR
Handwritten Text Recognition (HTR) system implemented with TensorFlow.
Site-Summary-Extraction
Application for fast query
unet
unet for image segmentation
Visualizing_Embeddings
A short tuitorial on how to Visualize Embeddings using Whatlies package and building a Classification Model