AWS SageMaker Practical for Beginners | Build 6 Projects
Master AWS SageMaker Algorithms (Linear Learner, XGBoost, PCA, Image Classification) & Learn SageMaker Studio & AutoML
In this course, students will learn how to create AI/ML models using AWS SageMaker. Projects will cover various topics from business, healthcare, and Tech. In this course, students will be able to master many topics in a practical way such as: (1) Data Engineering and Feature Engineering, (2) AI/ML Models selection, (3) Appropriate AWS SageMaker Algorithm selection to solve business problem, (4) AI/ML models building, training, and deployment, (5) Model optimization and Hyper-parameters tuning. The course covers many topics such as data engineering, AWS services and algorithms, and machine/deep learning basics in a practical way
Best Seller Course: AWS Certified Solutions Architect Associate – Step by Step
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.
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