Beyond Jupyter Notebooks
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Sale Page :_https://archive.md

What you’ll learn
Docker
Data Science
Jupyter
Python
Data Analysis
Data Visualization
Open Source
Requirements
Minimal Python Knowledge
Running Docker Installation
Fun exploring new topics
Description
Interactive notebooks like Jupyter have become more and more popular in the recent past and build the core of many data scientist’s workplace. Being accessed via web browser they allow scientists to easily structure their work by combining code and documentation. Yet notebooks often lead to isolated and disposable analysis artefacts. Keeping the computation inside those notebooks does not allow for convenient concurrent model training, model exposure or scheduled model retraining.
Those issues can be addressed by taking advantage of recent developments in the discipline of software engineering. Over the past years containerization became the technology of choice for crafting and deploying applications. Building a data science platform that allows for easy access (via notebooks), flexibility and reproducibility (via containerization) combines the best of both worlds and addresses Data Scientist’s hidden needs.
Who this course is for:
Any level of data scientists that want to accelerate their capabilities
Open Source Lover вќ¤пёЏ
Pythonistas interested in Docker

Beyond Jupyter Notebooks Contains: Video, PDF´s
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