Packt Publishing – Making Predictions with Data and Python
English | Size: 771.65 MB
Category: Tutorial
Python has become one of any data scientist’s favorite tools for doing Predictive Analytics. In this hands-on course, you will learn how to build predictive models with Python.
During the course, we will talk about the most important theoretical concepts that are essential when building predictive models for real-world problems. The main tool used in this course is scikit -learn, which is recognized as a great tool: it has a great variety of models, many useful routines, and a consistent interface that makes it easy to use. All the topics are taught using practical examples and throughout the course, we build many models using real-world datasets.
By the end of this course, you will learn the various techniques in making predictions about bankruptcy and identifying spam text messages and then use our knowledge to create a credit card using a linear model for classification along with logistic regression.
What You Will Learn
• Understand the main concepts and principles of Predictive Analytics and how to use them
when building real-world predictive models.
• Properly use scikit-learn, the main Python library for Predictive Analytics and Machine
Learning.
• Learn the types of Predictive Analytics problem and how to apply the main models and
algorithms to solve real world problems.
• Build, evaluate, and interpret classification and regression models on real-world datasets.
• Understand Regression and Classification
• Refresh your visualization skills
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