Model tuning

Model tuning

ByMichael Stainsbury

Hyperparameters can be thought of as the external controls that influence how the model operates, just as flight instruments control how an aeroplane flies. These values are external to the model and are controlled by the user. They can influence how an algorithm is trained and the structure of the final model. The optimized settings…

How to select a model for a given machine learning problem

How to select a model for a given machine learning problem

ByMichael Stainsbury

To select a model for a given Machine Learning problem we use the information and conclusions from Framing the Problem. A Machine Learning problem can be described with four aspects: The first aspect concerns the format and structure of the data, which could be numeric, images or text. Numeric data is often tabular. The second…

Deploy and operationalize machine learning solutions

Deploy and operationalize machine learning solutions

ByMichael Stainsbury

This Study Guide describes how to deploy a Machine Learning Model into the production environment and to monitor it once it is deployed. The foundations of a reliable production environment are good Software Management and Software Engineering. The emerging job role of ML Ops, which is derived from Dev Ops, is focused on delivering the…

Machine Learning services and features

Machine Learning services and features

ByMichael Stainsbury

Using SageMaker AI services is like visiting a well equipped gym, you just have to choose the right equipment for your goals. AWS has a wide range of Machine Learning services and capabilities, each one has its own advantages and disadvantages. Understanding your use case is key to selecting the most appropriate service. Scroll to…

AWS security for machine learning

AWS security for machine learning

ByMichael Stainsbury

Security is a vast subject and AWS even have their own Professional level certificate exam on this subject. Using the AWS course: Exam Readiness: AWS Certified Machine Learning – Specialty as a guide these revision notes give an overview of the main AWS security service Identity and Access Management (IAM) and then highlight security features…

Data transformation for Machine Learning

Data transformation for Machine Learning

ByMichael Stainsbury

This Study Guide is about transforming raw data so it is ready for Machine Learning. There are two types of transformation: Identify and implement a data-transformation solution is sub-domain 1.3 of the Data Engineering knowledge domain. For more information about the exam structure see: AWS Machine Learning exam syllabus Questions To confirm your understanding scroll to…

The Machine Learning Production Environment

The Machine Learning Production Environment

ByMichael Stainsbury

When you launch a Machine Learning solution in production it needs to perform well to provide the business benefit it was designed for. There are two types of performance: This Study Guide focuses on the production environment. The production environment can be assessed using five measures: There are three curated videos in this Study Guide:…

Data cleansing and preparation for modeling

Data cleansing and preparation for modeling

ByMichael Stainsbury

Understanding data, cleansing data and dataset generation are important first steps in exploratory data analysis. Every other phase in the Machine Learning process relies on the data being cleaned and prepared. This Study Guide starts with statistical techniques used to help understand the data. Once data is understood it has to be cleaned up so…