aymanibrahim / mlpy

Hands-on in-person workshop for Machine Learning with Python

Why

For people who struggle to start in machine learning with Python

Description

This hands-on in-person workshop is based on Machine Learning with Python Course by IBM Cognitive Class

Learn how to get started with supervised and unsupervised learning to uncover insights and predict future trends.

Outline

The workshop will cover core topics:

01 Intro

Applications	Supervised vs Unsupervised Learning	Prediction

• Applications of Machine Learning
• Python libraries for Machine Learning
• Supervised vs Unsupervised Learning

02 Regression

Linear Regression	Non-linear Regression	Evaluation

• Linear Regression
• Non-linear Regression
• Model evaluation methods

03 Classification

K-Nearest Neighbour	Decision Trees	Logistic Regression

• K-Nearest Neighbour
• Decision Trees
• Logistic Regression
• Support Vector Machines

04 Clustering

K-Means	Hierarchical	Density-Based Clustering

• K-Means Clustering
• Hierarchical Clustering
• Density-Based Clustering

05 Recommender Systems

Types	Content-based	Collaborative Filtering

• Content-based recommender systems
• Collaborative Filtering

Prerequisites

• Python for Data Science Workshop
• Data Analysis with Python Workshop

Pre-workshop

You will need a laptop that can access the internet

1: Installation

Install miniconda or install the (larger) Anaconda distribution

Install Python using Miniconda

OR Install Python using Ananconda

2: Setup

2.1: Download workshop code & materials

Clone the repository

git clone [e-mail]:aymanibrahim/mlpy.git

OR Download the repository as a .zip file

2.2: Change directory to pyds

Change current directory to mlpy directory

cd mlpy

2.3: Install Python with required packages

Install Python with the required packages into an environment named mlpy as per environment.yml YAML file.

conda env create -f environment.yml

When conda asks if you want to proceed, type "y" and press Enter.

3: Activate environment

Change the current default environment (base) into mlpy environment.

conda activate mlpy

4: Install & Enable ipywidgets extentions

Install ipywidgets JupyterLab extension

jupyter labextension install @jupyter-widgets/jupyterlab-manager

Enable widgetsnbextension

jupyter nbextension enable --py widgetsnbextension --sys-prefix

5: Check installation

Use check_environment.py script to make sure everything was installed correctly, open a terminal, and change its directory (cd) so that your working directory is the workshop directory mlpy you cloned or downloaded. Then enter the following:

python check_environment.py

If everything is OK, you will get the following message:

Your workshop environment is set up

6: Start JupyterLab

Start JupyterLab using:

jupyter lab

JupyterLab will open automatically in your browser.

You may access JupyterLab by entering the notebook server’s URL into the browser.

7: Stop JupyterLab

Press CTRL + C in the terminal to stop JupyterLab.

8: Deactivate environment

Change the current environment (mlpy) into the previous environment.

conda deactivate

Workshop Instructor

Ayman Ibrahim

• LinkedIn
• Kaggle
• GitHub
• Twitter
• Facebook

References

• Python: Programming language
• Conda: Package and environment manager
• Anaconda: Python distribution
• Miniconda: Minimal installer for conda
• NumPy: Fundamental package for scientific computing with Python
• Matplotlib: Python 2D plotting library
• seaborn: Statistical Data Visualization
• pandas: Python data analysis library
• scikit-learn: Machine Learning in Python
• Jupyter Notebook: Web application to create documents with code, equations, visualizations and text
• JupyterLab: Web-based development environment for Jupyter Notebooks
• Python for Data Science: Course by IBM Cognitive Class
• Data Analysis with Python: Course by IBM Cognitive Class
• Data Visualization with Python: Course by IBM Cognitive Class
• Machine Learning with Python: Course by IBM Cognitive Class

Contributing

Thanks for your interest in contributing! There are many ways to contribute to this project. Get started here.

License

Workshop Code

Workshop Materials

Machine Learning with Python Workshop by Ayman Ibrahim is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at IBM Cognitive Class Machine Learning with Python Course by Saeed Aghabozorgi, PhD and Agatha Colangelo.