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Python2 and Python3 are already installed on Debian 10, but the default version is Python2. How to check it...$ python

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language	bash

python --version

# That will return Python 2.x.x

Check for Python3
$ python3

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language	bash
theme	Confluence

python3 --version

# That will return Python 3.x.x

We have to make Python3 as the default version for the distro.
Firstly we have to find the directories for each version...$ ls

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language	bash
theme	Confluence

ls /usr/bin/python* -la

In this example it returns a bunch of directories...

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Now we must update/create the "Python alternatives list" using the above paths. $ sudo

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language	bash

sudo update-alternatives --install /usr/bin/python python /usr/bin/python2.7 1

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language	bash

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sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 2

Finally we can switch between Python versions. Running the following command, a menu will appear in order to choose the Python version that we want as default.

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sudo update-alternatives --config python

There are 2 choices for the alternative python (providing /usr/bin/python).

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Choosing the selection 2 then Python3 will become the default version.
We could check if Python3 has applied as default, running...

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language	bash

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python --version

# In my case it returns Python 3.7.3

2. Download and install Miniforge3

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But first check if there is the Download directory on your distro. If there is none, then create one...
$ mkdir

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mkdir ~/Download

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cd ~/Download

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sudo wget https://github.com/conda-forge/miniforge/releases/download/4.8.3-4/Miniforge3-Linux-aarch64.sh

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bash Miniforge3-Linux-aarch64.sh

* Miniforge3 will be installed at this location: ~/miniforge3/bin/ and add it to your PATH variable.
In order to check the location of executable "conda" file, type the following...

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language	bash

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sudo find / -type f -name "conda"

For In my case it returned "~/miniforge3/bin/" and the variable PATH must be changed to...
$ export

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export PATH=$PATH:~/miniforge3/bin

3. Install MLFlow using Conda

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language	bash

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conda install -c https://conda.anaconda.org/paulscherrerinstitute mflow

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conda update conda

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conda --version

# In my case the version is 4.9.2

`4. Create and activate a conda virtual environment and install MLFlow`

A conda environment is a directory that contains a specific collection of conda packages that you have installed. For example, you may have one environment with NumPy 1.7 and its dependencies. The name of the environment is env_mlflow. Use your Python's version to create an environment...

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language	bash

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conda create --name env_mlflow python=3.7.3

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conda activate env_mlflow

Reboot the machine and login again. If you are using a remote machine, reboot the remote instance and use ssh to login again.

After the reboot we can install MLFlow using pip3.

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pip3 install mlflow

`5.Install Sklearn using pip3 and other dependencies`

We need GCC and G++ compilers as dependencies to build Sklearn.

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sudo apt-get install gcc

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sudo apt-get install g++

This app helps us to save the point of the process, when the connection drops. As a result, when we reconnect, we can continue from the point where our process was disrupted and not from the very beginning.

(optional) Install tmux. It takes a lot of time to build Sklearn, and there is a high possibility the internet access will be lost. So, tmux helps us to continue the proccess from where it left off. $

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sudo apt-get install tmux

$ tmux # We open tmux environment Install sklearn To open tmux just type... tmux

Install Sklearn using pip3 and the dependencies. $ pip3 install sklearn $ pip3 install Cython $ pip3 install

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pip3 install sklearn
pip3 install Cython
pip3 install --upgrade setuptools

`6. Install Matplotlib`

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK+.$ conda install

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conda install -c conda-forge matplotlib

In order to check the installation...

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language	bash

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pip3 install matplotlib

# The return must be "Requirement already satisfied"

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PostgreSQL, also known as Postgres, is a free and open-source relational database management system emphasizing emphasising extensibility and SQL compliance. $ sudo

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language	bash

sudo apt-get install postgresql

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sudo apt-get install postgresql-contrib

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sudo apt-get install postgresql-server-dev-all

`8. Install Psycopg`

Psycopg is the most popular PostgreSQL database adapter for the Python programming language. Its main features are the complete implementation of the Python DB API 2.0 specification and the thread safety (several threads can share the same connection). $ pip3 install

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language	bash

pip3 install psycopg2

`9. Download and run MLFlow examples`

Check if Git is already installed...

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git --version

If the Git is not installed... $ sudo apt update $ sudo apt install

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sudo apt update
sudo apt install git

Clone MLFlow example code

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cd ~

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git clone https://github.com/mlflow/mlflow

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cd ~/mlflow/examples/sklearn_elasticnet_diabetes/linux

Run the example "train_diabetes"

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python train_diabetes.py 0.1 0.9

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python train_diabetes.py 0.5 0.5

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python train_diabetes.py 0.9 0.1

# For each example above the return must be something like this... RMSE: 71.98302888908191 MAE: 60.5647520017933 R2: 0.2165516143465459

MLflow runs can be recorded either locally in files or remotely to a tracking server. By default, the MLflow Python API logs runs to files in an mlruns directory wherever you ran your program. You can then run "mlflow ui" to see the logged runs.

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language	bash

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mlflow ui

# The return must be something like that... 2020-12-03 14:17:36 +0000] [1267] [INFO] Starting gunicorn 20.0.4 [2020-12-03 14:17:36 +0000] [1267] [INFO] Listening at: http://127.0.0.1:5000 (1267) [2020-12-03 14:17:36 +0000] [1267] [INFO] Using worker: sync [2020-12-03 14:17:36 +0000] [1270] [INFO] Booting worker with pid: 1270

At the 2nd line there is the localhost's IP and the port (127.0.0.1:5000). Now we can use them to get the results. Using a remote machine (OpenStack), the instances does not have a Desktop Environment (GNOME, XFCE, e.t.c.) in order to see the results. But we can check if it has created the "index.html" file at at http://127.0.0.1:5000... $ cd

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cd ~/Download

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wget 127.0.0.1:5000

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cat index.html

But, using SSH Tunneling we can see the OpenStack's instance localhost on the local Web browser. Syntax: ssh -L port:localhost:port userName@FloatingIP Example: ssh -L 5000:localhost:5000 debian@214.152.131.68 (We can replace the localhost with the 127.0.0.1)

Version	Old Version 5	New Version 6
Changes made by	Takis Mavrodakos (Deactivated)	Takis Mavrodakos (Deactivated)
Saved on	Dec 08, 2020	Dec 09, 2020

Versions Compared

Key

2. Download and install Miniforge3

3. Install MLFlow using Conda

`4. Create and activate a conda virtual environment and install MLFlow`

`5.Install Sklearn using pip3 and other dependencies`

`6. Install Matplotlib`

`8. Install Psycopg`

`9. Download and run MLFlow examples`