Name: Abbey
Type: User
Company: The University of the Witwatersrand, Johannesburg
Bio: I'm a PhD student in Computer Science with focus on natural language processing, computational linguistics, information extraction, and entity recognition.
Location: South Africa
Abbey's Projects
Similarity Learning for Authorship Verification
Code for Spooky Author Identification
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
The study aims to understand the public sentiments analysis in south africa in 2021 on Twitter during during looting
A collection of infrastructure and tools for research in neural network interpretability.
Practical Full-Stack Machine Learning
This contains the IPython notebooks describing Machine Learning algorithms I had used for the Kaggle contest "Microsoft Malware Classification Challenge".
🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
Some practices for ML Security, like XSS、Webshell detection...
Companion webpage to the book "Mathematics For Machine Learning"
MPST: Movie Plot Synopses with Tags
Multi Text Classificaiton
Codes, datasets, and explanations for some basic natural language tasks and models.
:memo: This repository recorded my NLP journey.
NLP model implementations with keras for beginner
Scikit-Learn, NLTK, Spacy, Gensim, Textblob and more
Essential and Fundametal aspects of Natural Language Processing with hands-on examples and case-studies
Some notes on Causal Inference, with examples in python
Support material for nucl.ai Conference 2016 workshops and open laboratories.
This repository contains all the code, models, scripts and reports for flagging probable vulnerabilities for the gokube-openshift eco-system
Using Pubmed data and tf.keras to predict if an ophthalmology paper will make it into a top 15 journal
EPFL Course - Optimization for Machine Learning - CS-439
Code used for evaluation and baselines in the PAN shared tasks.
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
📚 A practical approach to machine learning to enable everyone to learn, explore and build.
Practical notebooks for Khipu 2019, held in Universidad de la República in Montevideo.
Open-source tool to visualise your RAG 🔮