About This Class
Build, train, and deploy a machine learning model using SageMaker ; Data Wrangling for Machine Learning on AWS Cloud
This course is designed for the students who are at their initial stage or at the beginner level in learning the Machine Learning concepts integrated with cloud computing using the Amazon AWS Cloud Services.
This course focuses on what cloud computing is, followed by some essential concepts of Machine Learning. It also has practical hands-on lab exercises which covers a major portion of setting up the basic requirements to run projects on SageMaker
This course covers five (5) projects of different machine learning algorithms to help students learn about the concepts of ML and how they can run such projects in the AWS SageMaker environment. Below is list of projects that are covered in this course:
1- Titanic Survival Prediction
2- Boston House Price Prediction
3- Population Segmentation using Principal Component Analysis (PCA)
4- Population Segmentation using KMeans Clustering
5- Handwritten Digit Classification (MNIST Dataset) -> Capstone
Today Data Science and Machine Learning is used in almost all the industries, including automobile, banking, healthcare, media, telecom and others.
Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to prepare build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. SageMaker provides all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost.
Look forward to see you enroll in this class to learn Machine Learning in AWS SageMaker platform. Best of luck!