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Machine Learning with Python

Posted By Cluzter Ops3     September 30, 2020     151 views     0 likes    
Cognitive Class is powered by the technology and content provided by the IBM Developer Skills Network. IBM Developer Skills Network is a recognized source of top-quality courses on topics including artificial intelligence (AI), machine learning, data science, big data, analytics, databases, cloud...  more

Overview

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.
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.



More important, you will transform your theoretical knowledge in to practical skill using many hands-on labs.

Get ready to do more learning than your machine!

COURSE 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



PREREQUISITES FOR THIS COURSE



  • Python for data science



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 JupyterLab and it is one of the most popular tools used by data scientists. If you are not familiar with JupyterLab, 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.