![]() You can find installation instructions for Miniconda on their website, but if you're using Linux (e.g. You can skip Miniconda entirely if you prefer and install Jupyter Lab directly, however, I prefer using it to manage other environments too. It is a small, bootstrap version of Anaconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib and a few others. Miniconda is a free minimal installer for conda. then activate the new env: conda activate tf-gpu. These packages contain everything you need to run JupyterLab. Original story: open anaconda prompt, create a new env, say tf-gpu conda create -n tf-gpu. One approach I can recommend is to install and use Miniconda. conda install -c conda-forge -c plotly jupyter-dash. There are many different ways to get up and running with an environment that will facilitate our work. You can add R to Jupyter Notebook by typing the following command in the Anaconda Prompt: conda install -c r r-irkernel. We will write all of our code within a Jupyter Notebook, but you are free to use other IDEs.įigure 1 - A Jupyter Notebook being edited within Jupyter Lab. If you have Docker installed, you can install and use JupyterLab by selecting one of the many ready-to-run Docker images maintained by the Jupyter Team. We will be using Rust along with packages that will form our scientific stack, such as ndarray (for multi-dimensional containers) and plotly (for interactive graphing), etc. As such, we need the right tools and environments available in order to keep up with the examples and exercises. ![]() We are taking a practical approach in the following sections.
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