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This project uses spectrograms and scaleograms to predict human activity from sensor information.
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html
XGBoost + Optuna
An index of algorithms for learning causality with data
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
AWS EKS Kubernetes - Masterclass | DevOps, Microservices
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Code for Stanford CS224u
🌀 Stanford CS 228 - Probabilistic Graphical Models
Bringing vtk.js into Dash and Python
Data Science interview question by iNeuron
Docker Fundamentals
Kubernetes Fundamentals
Matt Brems' Missing Data Workshop
Natural Language Processing Workshop at ODSC West 2021
Machine Learning Operations (MLOps) are essential to build successful Data Science use-cases. Today, ML is powering data driven use-cases that are transforming industries around the world. In order to seize and hold it's competitive advantage business needs to reduce risk therefore a new expertise rises to include data science models in operational systems. According to Gartner Research “While many organizations have experimented with AI proofs of concept, there are still major blockers to operationalizing its development. IT leaders must strive to move beyond the POC to ensure that more projects get to production and that they do so at scale to deliver business value. (July 2020)”. In this session, we will discuss the role of MLOps and how they can help data science models from deployment to maintenance with focus on: keep track of performance degradation overtime from model predictions quality, setting up continuous evaluation metrics and tuning the model performance in both training and serving pipelines that are deployed in production.
A 3-hour workshop on data visualization in Python with notebooks and exercises for following along.
Repository for GNN tutorial using Pytorch and Pytorch Geometric (PyG) for ODSC 2021
🧮 Bayesian networks in Python
StackNet is a computational, scalable and analytical Meta modelling framework
trustworthy AI related projects
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.