Merge pull request #181 from microsoft/miguelgfierro-patch-1
Update conda in setup
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SETUP.md
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SETUP.md
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@ -28,6 +28,7 @@ Depending on the type of NLP system and the notebook that needs to be run, there
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* A machine running Linux, MacOS or Windows.
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* A machine running Linux, MacOS or Windows.
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* Anaconda with Python version >= 3.6.
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* Anaconda with Python version >= 3.6.
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* This is pre-installed on Azure DSVM such that one can run the following steps directly. To setup on your local machine, [Miniconda](https://docs.conda.io/en/latest/miniconda.html) is a quick way to get started.
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* This is pre-installed on Azure DSVM such that one can run the following steps directly. To setup on your local machine, [Miniconda](https://docs.conda.io/en/latest/miniconda.html) is a quick way to get started.
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* It is recommended to update conda to the latest version: `conda update -n base -c defaults conda`
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### Dependencies Setup
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### Dependencies Setup
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@ -64,4 +65,4 @@ We can register our created conda environment to appear as a kernel in the Jupyt
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conda activate my_env_name
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conda activate my_env_name
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python -m ipykernel install --user --name my_env_name --display-name "Python (my_env_name)"
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python -m ipykernel install --user --name my_env_name --display-name "Python (my_env_name)"
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If you are using the DSVM, you can [connect to JupyterHub](https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-ubuntu-intro#jupyterhub-and-jupyterlab) by browsing to `https://your-vm-ip:8000`.
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If you are using the DSVM, you can [connect to JupyterHub](https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/dsvm-ubuntu-intro#jupyterhub-and-jupyterlab) by browsing to `https://your-vm-ip:8000`.
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