Applied Machine Learning in Python

This course is part of Applied Data Science with Python Specialization

Instructor: Kevyn Collins-Thompson

What you'll learn

  •   Describe how machine learning is different than descriptive statistics
  •   Create and evaluate data clusters
  •   Explain different approaches for creating predictive models
  •   Build features that meet analysis needs

    • Skills you'll gain

  •   Applied Machine Learning
  •   Feature Engineering
  •   Predictive Modeling
  •   Machine Learning
  •   Supervised Learning
  •   Scikit Learn (Machine Learning Library)
  •   Dimensionality Reduction
  •   Random Forest Algorithm
  •   Unsupervised Learning
  •   Decision Tree Learning

    • There are 4 modules in this course

    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 Applied Social Analysis in Python.

    Module 2: Supervised Machine Learning - Part 1

    Module 3: Evaluation

    Module 4: Supervised Machine Learning - Part 2

    Explore more from Data Analysis

    Applied Machine Learning with Python

    Machine Learning with Python

    Unsupervised Machine Learning

    Cluster Analysis and Unsupervised Machine Learning in Python

    ©2025  ementorhub.com. All rights reserved