Learn the Basics of Machine Learning with IBM Watson Studio (W7L160G)

Overview

This course introduces a case study, data set, machine learning concepts, and developing a machine learning model with Watson Studio.

Initially, you will be introduced to the case study and the challenges company facing, and the company data set. Next, you will be introduced to supervised, unsupervised learning, deep and reinforcement learning algorithms. Finally, you will develop a supervised machine learning model IBM Watson Studio with the dataset provided using Python.

Audience

AI Specialists who want to learn machine learning algorithms

Prerequisites

  • Some experience in Python¬†
  • Some experience in Jupyter notebook¬†
  • Some experience in Watson Studio or completion of Watson Studio Primer
  • A Watson Studio Lite plan

Objective

  • Describe the use case and the data set
  • Distinguish between supervised and unsupervised machine learning
  • Define deep learning and reinforcement learning
  • Demonstrate the basic functions of Watson Studio for machine learning
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Course Outline

  • Introduction to the case study and the data set
  • Introduction to Machine Learning
  • Developing the model