This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and …

This repository contains solutions of all assignments of University of Michigan's Applied Machine Learning with python course.

Course materials for the Coursera MOOC: Applied Machine Learning in Python from University of Michigan, Course 3 of the Applied Data Science with Python Specialization

This module introduces basic machine learning concepts, tasks, and workflow using an example classification problem based on the K-nearest neighbors method, and implemented using the …

For this assignment, you will be using the Breast Cancer Wisconsin (Diagnostic) Database to create a classifier that can help diagnose patients. First, read through the description of the …

By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to …

Applied Machine Learning in Python. This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these …

Assignment 2¶ In this assignment you'll explore the relationship between model complexity and generalization performance, by adjusting key parameters of various supervised learning …

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