Python: Build Machine Learning Models in 6 Hours

Given the constantly increasing amounts of data they’re faced with, programmers and data scientists have to come up with better solutions to make machines smarter and reduce manual work along with finding solutions to the obstacles faced in between. Python comes to the rescue to craft better solutions and process them effectively.

This comprehensive 2–in–1 course teaches you how to perform different machine learning tasks along with fixing common machine learning problems you face in your day–to–day tasks. You will learn how to use labeled datasets to classify objects or predict future values, so that you can provide more accurate and valuable analysis. You will also use unlabelled datasets to do segmentation and clustering, so that you can separate a large dataset into sensible groups. Further to get a complete hold on the technology, you will work with tools using which you can build predictive models in Python.

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

In the first course, Getting Started with Machine Learning in Python, you will learn how to use labeled datasets to classify objects or predict future values, so that you can provide more accurate and valuable analysis. You will then use unlabelled datasets to do segmentation and clustering, so that you can separate a large dataset into sensible groups. You will also learn to understand and estimate the value of your dataset. Next, you will learn how to clean data for your application, and how to recognize which machine learning task you are dealing with.
The second course, Building Predictive Models with Machine Learning and Python, will introduce you to tools with which you can build predictive models with Python, the core of a Data Scientist’s toolkit. Through some really interesting examples, the course will take you through a variety of challenges: predicting the value of a house in Boston, the batting average of a baseball player, their survival chances had they been on the Titanic, or any other number of other interesting problems.