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Project involves the application of bayesian inference using python pgmpy library. The python script modelled the bayes net and obtained some probabilities based on the model.

Python 100.00%

artificial-intelligence bayes-net bayesian-inference machine-learning pgmpy

bayesian_inference's Introduction

Hi there! 👋 I'm Tobias

Fullstack Software Engineer passionate about mentorship, driving innovation and improving processes through scalable and maintainable software solutions.

🤵 About Me

🎓 Master's degree in Software Engineering.
⚙️ Specialized in GenAI, microservices, system integration, and process automation.
🚀 Proficient in collaborating with cross-functional teams and developing enterprise-level solutions.
📈 Committed to delivering clean, secure, maintainable, and user-centric solutions.
👥 Proud to have contributed to projects serving over 20M+ users.

⚙️ Skills

Languages & Frameworks: C, C#, Javascript, Typescript, Python, SQL, Java, .NET, Node.js, React, Next.js, J2EE, Angular
Databases - Oracle, Postgres, MSSQL, MySQL, MongoDB, Cassandra, Elasticsearch, qdrant, pinecone
Technologies: Linux, Windows, Git, gRPC, Airflow, Spark, Kibana, Logstash, Terraform, NUnit, AI/ML, Apache Spark, Protobuf, CI/CD, LangChain, OpenAI, MistralAI, Vitest
Tools: VSCode, Visual Studio, Postman, StarUML, WordPress, CircleCI, Slack, Notion, GitHub, Datadog, Docker, Jira, BluePrism, SonarQube, Scaleway, Vercel, Linear, Okta, Keycloak
Cloud Platforms: Azure, AWS, GCP

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