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This Machine Learning with Python course dives into the basics of machine learning using Python, 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.
We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such as Train/Test Split, Root Mean Squared Error (RMSE), and Random Forests. Along the way, you’ll look at real-life examples of machine learning and see how it affects society in ways you may not have guessed!
Most importantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
We'll explore many popular algorithms including Classification, Regression, Clustering, and Dimensional Reduction and popular models such asTrain/Test Split, Root Mean Squared Error and Random Forests.
Mostimportantly, you will transform your theoretical knowledge into practical skill using hands-on labs. Get ready to do more learning than your machine!
- The difference between the two main types of machine learning methods: supervised and unsupervised
- Supervised learning algorithms, including classification and regression
- Unsupervised learning algorithms, including Clustering and Dimensionality Reduction
- How statistical modeling relates to machine learning and how to compare them
- Real-life examples of the different ways machine learning affects society
Prerequisite
Syllabus
Module 1 - Introduction to Machine Learning
Applications of Machine Learning
Supervised vs Unsupervised Learning
Python libraries suitable for Machine Learning
Module 2 - Regression
Linear Regression
Non-linear Regression
Model evaluation methods
Module 3 - Classification
K-Nearest Neighbour
Decision Trees
Logistic Regression
Support Vector Machines
Model Evaluation
Module 4 - Unsupervised Learning
K-Means Clustering
Hierarchical Clustering
Density-Based Clustering
Module 5 - Recommender Systems
Content-based recommender systems
Collaborative Filtering
Instructors
Saeed Aghabozorgi
PhD, Sr. Data Scientist
IBM
Content Designer
International Business Machines Corporation, known by its acronym IBM, is an American multinational computer hardware, software and services company.
The company was formed on 16 June 1911 from the merger of the Computing Scale Company and the Tabulating Machine Company under the name Computing Tabulating Recording Company (CTR). It changed its name to International Business Machines Corporation on 14 February 1924. It was given the nickname Big Blue in reference to the dark blue colour long associated with the company. In the 1970s and 1980s, IBM was the world's largest market capitalisation.
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resourceful with applicable tips and educative
resourceful with applicable tips and educative
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