sdjoko Goto Github PK
Type: User
Type: User
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage deep learning and deep transfer learning to solve popular tasks in NLP including Classification, Information Retrieval, Sentiment Analysis, Search Engines, Clustering, Paraphrase Mining, Summarization, Language Translation, Q&A systems
Code files for advanced LLM Course
Python library for adversarial machine learning (evasion, extraction, poisoning, verification, certification) with attacks and defences for neural networks, logistic regression, decision trees, SVM, gradient boosted trees, Gaussian processes and more with multiple framework support
Discrimination free Naive Bayes
Bias and Fairness Audit Toolkit
Adaptive Monte Carlo Multiple Testing
detect demographic differences in the output of machine learning models or other assessments
A curated list of awesome adversarial machine learning resources
A curated list of awesome algorithmic fairness resources.
A curated list of awesome Fairness in AI resources
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
A curated list of awesome machine learning interpretability resources.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
how to evaluate use case, compare LLMs, and UI
Data and analysis for 'Machine Bias'
Quiz Answers, Assessments, Programming Assignments for the Linear Algebra course.
Code of the solutions of the Mathematics for Machine Learning course taught in Coursera.
Materials for a short course on convex optimization.
Keras implementation for DASP: Deep Approximate Shapley Propagation (ICML 2019)
A curated, but incomplete, list of data-centric AI resources.
Public repository for the "Data-Centric Deep Learning" course taught by Mike Wu and Andrew Maas. Available at https://corise.com/course/data-centric-deep-learning.
common data analysis and machine learning tasks using python
Remove problematic gender bias from word embeddings.
Materials and resources for Debugging Data Science LiveTraining
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.