Welcome to the machine learning quick start guide course. We're pleased to present to you a very fast paced introduction into the world of machine learning.
The goal for this training is to teach you the basic concepts and tools to succesfully build your first machine learning project and bring it to production.
- HOUR 1 - Introduction into ML
- HOUR 2 - Doing maths with numpy
- HOUR 3 - Data wrangling with pandas
- HOUR 4 - Lab: Exploring data with numpy and pandas
- HOUR 5 - Machine learning with scikit-learn
- HOUR 6 - Lab: Building your own machine learning model
- HOUR 7 - Setting up a machine learning project with cookiecutter templates
- HOUR 8 - Lab: Setting up your project with cookiecutter templates
- HOUR 9 - Introduction to running experiments with Azure Machine Learning Service
- HOUR 10 - Lab: Running your project as an experiment in Azure Machine Learning Service
- HOUR 11 - Deploying models to production with Azure Machine Learning Service
- HOUR 12 - Lab: Deploying your model to production
For this course you need the following tools on your machine:
After you've set up the requirements, you're ready to watch the slides and try out the labs in this course.
We've stored all the materials as reveal.js slidedecks in this repository. To watch the slides, follow these steps.
- First, clone the repository to disk.
- Next, install revelation with the command
pip install revelation - Then, run the command
revelation start slides/<module-name>/slides.mdto start the presentation.
Please navigate to the folder labs to find the labs for this course.
We've split the labs into various subfolders that match the hours in the
table of contents above.
This course uses reveal.js through the revelation python package.
You can use the S in any presentation to pull up the speaker notes.
Every slide deck takes 60 minutes to work through. A pacing timer is included so you have an idea how fast you're going to through the materials.