<p>You're looking for a complete classification modeling course that teaches you everything you need to create a classification model in Python, right? You've found the right classification modeling course! </p><p> </p><p>After completing this course you will be able to: </p><p>- Identify business problems that can be solved using machine learning classification modeling techniques. </p><p>- Create different classification modeling models in Python and compare their performance. </p><p>- Confidently practice, discuss and understand machine learning concepts </p><p> </p><p>If you are a business manager, an executive, or a student and want to learn and apply machine learning in real-world business problems, this course will give you a solid base by teaching you the most popular ML classification, such as Logistic Regression, Linear Discriminant Analysis, and KNN. This course teaches you all the steps you need to follow to create a Linear Regression model (the most popular Machine Learning model) to solve business problems. They also look at how to quantify model performance using a confusion matrix, how categorical variables in independent variables datasets are interpreted, how to implement a test-train split and to interpret the result to find out the answer to a business problem. </p><p> </p><p>By the end of this course, your confidence in creating a classification model in Python will have soared. You'll have a thorough understanding of how to use classification modeling to create predictive models and solve business problems. </p><p> </p><p>All the code and supporting files for this course are available at - https://github.com/PacktPublishing/Logistic-Regression-LDA-and-KNN-in-Python-for-Predictive-Modeling</p>