vigneshprajapati's starred repositories
parallel_selenium_dynamic_web_scraping
parallel-selenium_dynamic_web-scraping
machinelearning
Machine learning and artificial intelligence
AuthorExtractor
Source code for the Medium article "Extracting the author of news stories with DOM-based segmentation and BERT"
twds-crawler
Highly scalable webcrawler for towardsdatascience.com by using Python, Selenium, Docker, Kubernetes and the infrastructure of the Google Cloud Platform
MLInterview
:octocat: A curated awesome list of AI Startups in India & Machine Learning Interview Guide. Feel free to contribute!
InvoiceNet
Deep neural network to extract intelligent information from invoice documents.
a-PyTorch-Tutorial-to-Sequence-Labeling
Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling
Scene-text-recognition
Scene text detection and recognition based on Extremal Region(ER)
CamScanner-In-Python
Build your own document scanner with OpenCV Python
word2vec-from-scratch-with-python
A very simple, bare-bones, inefficient, implementation of skip-gram word2vec from scratch with Python
vue-burger-menu
🍔 An off-canvas sidebar Vue component - https://vue-burger-menu.netlify.app/
vue-mugen-scroll
Infinite scroll component for Vue.js 2
flask-full
starter/boilerplate flask application with celery, mongoengine, signals, shell commands, swagger api docs and sphinx docs integration
ML-From-Scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
autocomplete
Autocomplete - an adult and kid friendly exercise in creating a predictive program
keras-chatbot-web-api
Simple keras chat bot using seq2seq model with Flask serving web
DeepLearningMovies
Kaggle's competition for using Google's word2vec package for sentiment analysis
list_of_recommender_systems
A List of Recommender Systems and Resources
fastai_notes
My classnotes, experiments, reproducible notebooks from fast.ai Deep Learning Class (v2) October 2017 cohort.
ML-From-Scratch
Python implementations of Machine Learning models and algorithms from scratch. Aims to cover everything from Data Mining techniques to Deep Learning.