Getting Started with Machine Learning Models

Developed with Calculated Systems
OverviewStepsAuthor
Calculated Systems
This content is developed in partnership with Calculated Systems
DifficultyIntermediate
AVG Duration4h
Students11
Content
Course Created with Sketch. 2 Exams Created with Sketch. 1 Labs Created with Sketch. 5

Description

This learning path explores the core concepts of machine learning, the models available, and how to train them. We’ll take a deeper look at what it means to train a machine learning model, as well as the data and methods required to do so. We’ll also provide an overview of the most common models you’re likely to encounter, and take a practical approach to understand when and how to use them to solve business problems. We then do a structured walkthrough on a series of case studies that will show you how to apply the concepts covered in this course to real-life examples.

We then try out the concepts covered in the course with practical labs. 

Learning Objectives

  • Understand the key concepts and models related to machine learning
  • Learn how to use training data sets with machine learning models
  • Learn how to choose the best machine learning model to suit your requirements
  • Understand how machine learning concepts can be applied to real-world scenarios in property prices, health, animal classification, and marketing activities

Intended Audience

This learning path is intended for anyone who is:

  • Interested in understanding machine learning models on a deeper level
  • Looking to enrich their understanding of machine learning and how to use it to solve complex problems
  • Looking to build a foundation for continued learning in the machine learning space and data science in general

Prerequisites

To get the most out of this learning path, you should have a general understanding of data concepts as well as some familiarity with cloud providers and their managed services, especially Amazon or Google. Some experience in data or development is preferable but not essential.

Feedback

If you have any feedback relating to this course, feel free to contact us at support@cloudacademy.com

Certificate

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Learning Path Steps

1courses

This course explores the core concepts of machine learning, the models available, and how to train them.

2courses

This course provides a practical understanding of the steps required to build and deploy machine learning models using Amazon SageMaker.

3labs

This lab is aimed at machine learning beginners who want to understand how to train custom models.

4labs

In this lab, you'll learn how to perform K-Means Clustering on a set of data and plot the outcome.

5labs

In this lab, you'll learn how to utilize SQL aggregate functions and utilize complex functions, and learn how to get complex insights from your data.

6labs

This lab will walk you through the changing database schema requirements of a bug tracking application and how to handle them.

7labs

This lab will dive into understanding GET, POST, DELETE, and PATCH HTTP verbs and will teach you to use Python to interact with an REST API.

8exam-filled

Final Exam: Getting Started with Machine Learning Models

About the Author
Students1969
Labs14
Courses8
Learning paths11

Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity.  With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing  decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.