AWS SageMaker Practical for Beginners | Build 6 Projects
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 7.33 GB | Duration: 14.5 hours

==========
What you'll learn
Train and deploy AI/ML models using AWS SageMaker
Optimize model parameters using hyperparameters optimization search.
Develop, train, test and deploy linear regression model to make predictions.
Deploy production level multi-polynomial regression model to predict store sales based on the given features.
Develop a deploy deep learning-based model to perform image classification.
Develop time series forecasting models to predict future product prices using DeepAR.
Develop and deploy sentiment analysis model using SageMaker.
Deploy trained NLP model and interact/make predictions using secure API.
Train and evaluate Object Detection model using SageMaker built-in algorithms.

Requirements
Basic knowledge of programming
Basic knowledge in AWS
Basic knowledge in machine learning
Description
Machine and deep learning are the hottest topics in tech! Diverse fields have adopted ML and DL techniques, from banking to healthcare, transportation to technology.

AWS is one of the most widely used ML cloud computing platforms worldwide – several Fortune 500 companies depend on AWS for their business operations.

SageMaker is a fully managed service within AWS that allows data scientists and AI practitioners to train, test, and deploy AI/ML models quickly and efficiently.

In this course, students will learn how to create AI/ML models using AWS SageMaker.

Download