Machine learning uses computers to run predictive models that learn from existing data in order to forecast future behaviors, outcomes, and trends.
In this data science course, you will be given clear explanations of machine learning theory combined with practical scenarios and hands-on experience building, validating, and deploying machine learning models. You will learn how to build and derive insights from these models using R, Python, and Azure Machine Learning.
Understand the operation of classifiers
Use logistic regression as a classifier
Understand the metrics used to evaluate classifiers
Lab: Classification with logistic regression taught using Azure Machine Learning
Regression in machine learning
Understand the operation of regression models
Use linear regression for prediction and forecasting
Understand the metrics used to evaluate regression models
Lab: Predicting bike demand with linear regression taught using Azure Machine Learning
How to improve supervised models
Process for feature selection
Understand the problems of over-parameterization and the curse of dimensionality
Use regularization on over-parameterized models
Methods of dimensionality reduction Apply cross validation to estimating model performance
Lab: Improving diabetes patient classification using Azure Machine Learning
Lab: Improving bike demand forecasting using Azure Machine Learning
Details on non-linear modeling
Understand how and when to use common supervised machine learning models Applying ML models to diabetes patient classification
Applying ML models to bike demand forecasting
Understand the principles of unsupervised learning models
Correctly apply and evaluate k-means clustering models
Correctly apply and evaluate hieratical clustering model
Lab: Cluster models with AML, R and Python
Understand the operation of recommenders
Understand how to evaluate recommenders
Know how to use alternative to collaborative filtering for recommendations
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.