Machine Learning - get value out of your data

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Understand the concepts of Machine Learning

Data is at the core of all business decisions. Machine learning is increasingly used to extract value from data and making improved decisions that keep a company ahead of the competition.

In this course you’ll be introduced to the concepts and applications of Machine Learning. You will learn various supervised and unsupervised ML algorithms and prediction tasks applied to different data. Moreover, by taking this course you’ll be able to understand how to choose the right model for your data.

Machine Learning Concepts
Machine Learning is not a new field, but it has received a lot of attention in recent years as an important tool when it comes to handling big data and building the AI applications of the future. Machine Learning models are now being used to solve many different problems, from predicting when industrial machinery needs replacement to unlocking our phones by recognizing our face.

With machine learning it becomes possible to build systems that improve with more data, which is a fundamentally different approach compared to traditional rule-based programming. This course will introduce the concepts of machine learning to allow participants to recognize problems that are best approached with machine learning.

The course has a number of hands-on exercises that will allow participants to gain practical experience with training and evaluating machine learning models for a range of different types of problems. Are you trying to extract insight from a large data set? Then this Machine Learning course is for you.

This introductory course is aimed at anyone curious to know more about Machine Learning and looking for an understanding of simple yet effective Machine Learning tools.

Your background is not crucial but most likely you are already working with large amounts of data today and want to learn how best to get value out of these.

Are you working with large data sets? Then this Machine Learning course is for you

This introductory course is aimed at anyone curious to know more about Machine Learning and looking for an understanding of simple yet effective Machine Learning tools.

Your background is not crucial but most likely you are already working with large amounts of data today and want to learn how to get the best value out of these.

Prerequisites

Basic coding or scripting knowledge is required.

After this course you will be able to:

On completing the course, you will be able to:

• Recognize different business problems that could be addressed using the potential of machine learning and artificial intelligence.
• Identify when to use machine learning to explain certain behaviors and when to use it to predict future outcomes.
• Understand how machine learning can be applied to numerical, text and image data.
• Clean and prepare data, perform Exploratory Data Analysis (EDA) and train classification model
• Identify the differences between some of the most popular machine learning models.
• Evaluate how good a machine learning model is and how to incorporate best practices.

After this course, the organization will:
Gain a competitive advantage by having employees with machine learning knowledge. And will be able to prepare for the future by collecting data suitable for machine learning

Course agenda on Machine Learning

The two-day course will be instructor led with hands-on exercises. The focus will be on giving the participants the knowledge and the confidence to apply machine learning to problems that they face in their own work. The course will touch upon many aspects of machine learning, but emphasis will be on classification tasks.

Participants are expected to bring own laptop to the class, everything else needed for the course is provided.

The hands-on exercises will be completed either locally on the participants laptop or in a cloud-based editor. In the latter case, participants should have or be willing to sign up for a free Google account.