Michael Nelz-ML-Engineer mit GenAI-Erfahrung

Management Von Data-Science-Teams (4+ Jahre)

Datenanalyse, Machine Learning Mit Python (10+ Jahre)

Deep Learning, Computer Vision Mit Python (8+ Jahre)

Prompt-Engineering Und Agentic Ai Mit Python (4+ Jahre)

Agiles Software Development (8+ Jahre)

Ml-Ops Und Data-Pipelines In Azure (6+ Jahre)

Knowledge Sharing (Coding Workshops, Kurse) (7+ Jahre)

Software-Entwicklung: Python, Java, C#, Html, Php, Javascript, Bash-Scripting (10+ Jahre)

Unit- Und E2e-Tests (6+ Jahre)

Python (Oop, Scripting, Jupyter Notebooks): Azure-Sdk, Fastapi, Flask, Keras, Langchain, Mlflow, Numpy, Openai, Opencv-Python, Pandas, Pep8, Pyspark, Pytest, Requests, Sagemaker, Setuptools, Scikit-Learn, Scipy, Statsmodels, Tensorflow

Generative Ki: Prompt-Engineering, Langchain, Langsmith, Llms, Agents

Bereitstellung: Gnu Make, Git, Github, Kubernetes (Kubectl), Kubeflow, Docker, Bash/Powershell, Postman, Helm-Charts, Vms, Cuda, Cudnn

Microsoft Azure-Stack: Ci/Cd-Pipelines (Yaml + Jenkins), Azure Devops, Azure Blob-Stores, Azure Sql, Azure Machine Learning, Azure Data Factory, Azure Openai, Azure Foundry, Azure Cli, Grafana

Aws-Stack: Amazon Sagemaker, S3, Cloudwatch, Iam

Gcp-Stack: Vertex Ai, Sql, Iam, Vms

Dokumentation: Latex, Markdown, Swagger, Draw.Io

Databricks, Hadoop, Hdfs, Apache Hive, Apache Zeppelin

Knime, Dataiku, Tableau, Board, Powerbi

R (Scripting, Markdown, Oop (S3, S4)): Dplyr, Ggplot2, Lattice, Leaflet, Stringr, Plotly, Shiny, Tidyr, Mlr3, Tensorflow, Caret

Sql