Welcome
IPN-Dharma AI Lab
This is an IPN CIC - DHARMA initiative to provide an Artificial Intelligence Laboratory to motivate researchers, professors and students to take advantage of the courses, resources and tools of the main technology platforms of the industry in the areas of Machine Learning, Data Science, Cloud Computing, Artificial Intelligence and Internet of Things with the purpose of generating a practical experience through a learning model between peers and by objectives.
Level 1: Literacy and Foundations
Machine Learning: Regression, Classification, and Clustering
Welcome to the Machine Learning: Regression, Classification, and Clustering Learning Path! The content in this learning path pairs with in person workshops that run in Microsoft Reactors and are standalone learning resources (you don't have to come to a workshop to benefit from these modules). Throughout this Learning Path you will be encouraged to test out Python code in Visual Studio Code (VS Code) using the Python extension and Jupyter Notebooks.
In this learning path, you'll:
In this learning path, you'll:
- Learn ways to prepare data for analysis.
- Make predictive models with variations of linear regression.
- Make predictions on non-linear data with regression.
- Build logistic regression and support vector machine models.
- Learn about results obtained with the k-means algorithm.
Courses in this program
1) Join and Clean Datasets: Deep dive
Learn how to join and clean datasets and prepare your data for analysis.
In this module, you will:
In this module, you will:
- Learn ways to prepare data for analysis.
- Dive deeper into cleaning and joining datasets Complementary content for Microsoft Reactor Workshops.
Estimated effort 1 hour
English language
2) Supervised Learning: Regression
Learn about linear regression models, and how to interpret their results.
In this module, you will:
In this module, you will:
- Learn to fit linear-regression models.
- Become familiar with interpreting the output of linear-regression models.
3) Unsupervised Learning: Clustering
Learn about k-means clustering - how to use it, the kinds of results to expect, and how to interpret the data.
In this module, you will:
In this module, you will:
- Learn about the kinds of results obtained with the k-means algorithm.
- Get basic knowledge about how to interpret those results.