
Course Overview
Machine learning is becoming huge business in the days of big data and huge web sites. This course will introduce the participants to data science and machine learning in particular reviewing and training using the most popular algorithms. The course will teach machine learning using python and will emphasize the stengths and weaknesses of the most popular algorithms.
Intended Audience / Who should attend
- Programmers or Exact Sciences people who wish to understand and utilize machine learning.
- Life science or social science people who has an affinity to computing and want to utilize machine learning in their research.
- Web site and mobile application developers who would like to use their data to do various predictions and analysis.
Exercises
Using Python: numpy, scipy, pandas, scikit-learn.
Prerequisites
- Background in mathematics or math affinity.
- Background in computing.
- Python programming at a basic level.
- Stastical affinity is a plus but is not required.
Notes
- This course does not include python basics which is a pre-requisite to this course.
- This course does not include deep learning which should be taken after this course.
After attennding the course attendees should be able to
- Use Python to do data analysis and visualization.
- Understand the differneces between the various ML algorithms, their strengths and weaknesses and what algorithm to apply when confronment with a problem.
- Apply common machine learning algorithms to predict various results.
- Understand the machine learning life cycle of a real world project.