No more Python env and package update. In this article, you will learn how to run Jupyter on Docker.
_Docker simplifies and accelerates your workflow, while giving developers the freedom to innovate with their choice of tools, application stacks, and deployment environments for each project. — from [Developing with Docker_](https://www.docker.com/why-docker)
Docker provides a contained environment for your development. By using Docker, you may not need to install pyenv/pipenv/virtualenv or any programming languages on your computer. You just use a Docker container! In this article, you will learn how to run Jupyter on Docker.
Install Docker Desktop and when you start Docker you will see an icon in the menu bar.
Docker menu on Mac. Image by Author
The Docker Preferences menu allows you to configure your Docker settings such as installation, updates, version channels, Docker Hub login, and more. Open Preferences and go to Resources to change CPUs, Memory, and other setups. By default, Docker Desktop is set to use half the number of processors available on the host machine.
Docker Preferences. Image by Author
Why Jupyter Notebooks are the Future of Data Science. How Jupyter Notebooks played an important role in the incredible rise in popularity of Data Science and why they are its future.
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A mini-guide that introduces the use of Docker’s containers for your data science needs & projects. One of the preliminary steps that you take when you embark on your data science journey is dealing with the installation of different software such as Python, Jyupter Notebook, some IDEs and countless libraries.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.