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Name: AVoss
Type: User
Bio: Data Scientist, Statistician
Location: Munich
Name: AVoss
Type: User
Bio: Data Scientist, Statistician
Location: Munich
Streamlit dashboard for time series anomaly detection
This is a workshop designed for Amazon Bedrock a foundational model service.
This is the source code for How to move your on-prem machine learning models into Amazon SageMaker - A Beginners Guide. The guide demonstrates a step by step approach to migrate you machine learning (ML) models from any place into Amazon SageMaker
AWS CDK workshop resources
Microsoft Azure Fundamentals - AZ-900T00 and AZ-900T01
Python code for bayesian optimization using Gaussian processes
Methods to get the probability of a changepoint in a time series.
R code for paper 'Bayesian model selection for unit root testing with multiple structural breaks'
Implementation of the Bayesian Sets algorithm and variants
Bayesian Data Analysis demos for Python
A Python library for Bayesian Anomaly Detection
Python implementation for Bernoulli mixture model inference via EM + MCMC
Coursera course : "A Crash Course in Causality: Inferring Causal Effects from Observational Data"
Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832
Material from Deeplearning.ai course: Generative AI with Large Language Models
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai
Dropout as Regularization and Bayesian Approximation
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Deeplearning.ai course on Generative Adversarial Networks
Python code for Gaussian mixture model
Demo of a simple way to use GitHub Actions to build your Python package, bump the version number, and publish it to GitHub releases and PyPI.org all with a single click of a button in the web interface.
Probabilistic time series modeling in Python
Gaussian Process Optimization using GPy
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.