In a nutshell, a virtual environment is a named, isolated, working copy of Python that that maintains its own files, directories, and paths so that you can work with specific versions of libraries or Python itself without affecting other Python projects.

Why the Need for Virtual Environments?

At its core, the main purpose of Python virtual environments is to create an isolated environment for Python projects. This means that each project can have its own dependencies, regardless of what dependencies every other project has.

Create virtual environments with Anaconda

With conda, you can create, export, list, remove, and update environments that have different versions of Python and/or packages installed in them…

Photo by Markus Spiske on Unsplash

Anaconda is a free and open-source distribution of the Python and R programming languages that is widely used among the Data Science, Machine Learning and Artificial Intelligence communities. However, due to its wide distribution, sometimes there is a need for complete removal or uninstall.

Here are some simple guides on how to uninstall or remove Anaconda completely from macOS computers.

Option A: Use simple remove to uninstall Anaconda:

Delete the anaconda install folder, which is usually under your home directory from your terminal:

*For macOS (High Sierra), Anaconda is installed at ~/opt/anaconda3.

rm -rf ~/anaconda3

Once you removed all the…

I found out upon updating my MacBook Pro to the latest macOS Catalina, Anaconda3 is no longer working with the latest zsh shell terminal. Command such as:

jupyter notebook

is no longer working.

The work around for this problem is to copy the codes from ~/.bash_profile to ~/.zshrc

For example, here are the codes from my ~/.bash_profile.

Simply type the following code in your terminal.

open ~/.bash_profile

and you can see the following codes:

# added by Anaconda3 5.2.0 installer
export PATH="/anaconda3/bin:$PATH"
# added by Anaconda3 2019.07 installer
# >>> conda init >>>
# !! Contents within this block are managed by 'conda init'…

With the recent interest in Artificial Intelligence, Machine Learning and Data Analytics, one of the biggest hurdles for Machine Learning Engineer, Data Scientist and Data Analyst is allocate the right hardware for model training. However, now it is possible for anyone to kick off model training with Google Colab.


Data science, machine learning and big data analytics enthusiast

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