This course aims to put the entire world of machine learning with AWS in front of you. Machine learning has become the new black. Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. The challenge in today’s world is the explosion of data from existing legacy data and incoming new structured and unstructured data. The complexity of discovering, understanding, performing analysis, and predicting outcomes on the data using machine learning algorithms is a challenge. Following AWS simplifying Machine learning, this course will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection.
This course will help solve everyday challenges you face as a data scientist. It begins with the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Then, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK.
At the end of this course, you will be a master at Amazon machine learning and have enough expertise to be able to build complex machine learning projects using AWS.