Join Course
Machine Learning with Python Training
This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!
Explore many algorithms and models:
-
Popular algorithms: Classification, Regression, Clustering, and Dimensional Reduction.
-
Popular models: Train/Test Split, Root Mean Squared Error, and Random Forests.
Get ready to do more learning than your machine!
COURSE SYLLABUS
Module 1 - Supervised vs Unsupervised Learning
-
Machine Learning vs Statistical Modelling
-
Supervised vs Unsupervised Learning
-
Supervised Learning Classification
Module 2 - Supervised Learning I
-
Reliability of Random Forests
-
Advantages & Disadvantages of Decision Trees
Module 3 - Supervised Learning II
-
Model Evaluation: Overfitting & Underfitting
-
Understanding Different Evaluation Models
Module 4 - Unsupervised Learning
-
K-Means Clustering plus Advantages & Disadvantages
-
Hierarchical Clustering plus Advantages & Disadvantages
-
Measuring the Distances Between Clusters - Single Linkage Clustering
-
Measuring the Distances Between Clusters - Algorithms for Hierarchy Clustering
Module 5 - Dimensionality Reduction & Collaborative Filtering
-
Dimensionality Reduction: Feature Extraction & Selection
-
Collaborative Filtering & Its Challenges
PREREQUISITES
RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE
-
You have to do hands-on lab for this course. The tool that you use for hands-on is called Jupyter and it is one of the most popular tools used by data scientists. If you are not familiar with Jupyter, I would recommend that you take our free Data Science Hands-on with Open Source Tools.
-
This hands-on lab requires that you have working knowledge of Python programming language as it applies to data analytics. If you don't feel you have sufficient skill in Data Analysis with Python, I recommend you take Data Analysis with Python courses.