Learn how to use the machine learning (ML) pipeline with Amazon SageMaker with hands-on exercises and four days of instruction. You will learn how to frame your business problems as ML problems and use Amazon SageMaker to train, evaluate, tune, and deploy ML models. Hands-on learning is a key component of this course, so you’ll choose a project to work on, and then apply the knowledge and skills you learn to your chosen project in each phase of the pipeline. You’ll have a choice of projects: fraud detection, recommendation engines, or flight delays.
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Learn how to use the machine learning (ML) pipeline with Amazon SageMaker with hands-on exercises and four days of instruction. You will learn how to frame your business problems as ML problems and use Amazon SageMaker to train, evaluate, tune, and deploy ML models. Hands-on learning is a key component of this course, so you’ll choose a project to work on, and then apply the knowledge and skills you learn to your chosen project in each phase of the pipeline. You’ll have a choice of projects: fraud detection, recommendation engines, or flight delays.
Was Sie in diesem Kurs lernen:
Dieser Kurs ist konzipiert für:
We recommend that attendees of this course have:
Dieser Kurs setzt sich zusammen aus:
Module 0: Introduction
• Pre-assessment
Module 1: Introduction to Machine Learning and the ML Pipeline
• Overview of machine learning, including use cases, types of machine learning, and key concepts
• Overview of the ML pipeline
• Introduction to course projects and approach
Module 2: Introduction to Amazon SageMaker
• Introduction to Amazon SageMaker
• Demo: Amazon SageMaker and Jupyter notebooks
• Hands-on: Amazon SageMaker and Jupyter notebooks
Module 3: Problem Formulation
• Overview of problem formulation and deciding if ML is the right solution
• Converting a business problem into an ML problem
• Demo: Amazon SageMaker Ground Truth
• Hands-on: Amazon SageMaker Ground Truth
Module 3: Problem Formulation (continued)
• Practice problem formulation
• Formulate problems for projects
Checkpoint 1 and Answer Review
Module 4: Preprocessing
• Overview of data collection and integration, and techniques for data preprocessing and visualization
• Practice preprocessing
• Preprocess project data and discuss project progress
Checkpoint 2 and Answer Review
Module 5: Model Training
• Choosing the right algorithm
• Formatting and splitting your data for training
• Loss functions and gradient descent for improving your model
• Demo: Create a training job in Amazon SageMaker
Module 6: Model Evaluation
• How to evaluate classification models
• How to evaluate regression models
• Practice model training and evaluation
• Train and evaluate project models, then present findings
Checkpoint 3 and Answer Review
Module 7: Feature Engineering and Model Tuning
• Feature extraction, selection, creation, and transformation
• Hyperparameter tuning
• Demo: SageMaker hyperparameter optimization
• Practice feature engineering and model tuning
• Apply feature engineering and model tuning to projects
• Final project presentations
Module 8: Deployment
• How to deploy, inference, and monitor your model on Amazon SageMaker
• Deploying ML at the edge
• Demo: Creating an Amazon SageMaker endpoint
• Post-assessment
• Course wrap-up
WICHTIG: Bitte bringen Sie zu unseren Trainings Ihr Notebook (Windows, Linux oder Mac) mit. Wenn dies nicht möglich ist, nehmen Sie bitte mit uns vorher Kontakt auf.
Kursunterlagen sind in englischer Sprache, Kurssprache des Trainers ist deutsch.
Datum | Kurs | Preis pro TN | ||
---|---|---|---|---|
02.08.2022 - 05.08.2022 | The Machine Learning Pipeline on AWS Teilnahme über Laptop o. PC mit Internetzugang. in - Online-Classroom - | 2.795,00 € zzgl. MwSt. | Buchen | |
02.08.2022 - 05.08.2022 | The Machine Learning Pipeline on AWS Vahrenwalder Straße 156 in 30165 Hannover | 2.795,00 € zzgl. MwSt. | Buchen | |
29.11.2022 - 02.12.2022 | The Machine Learning Pipeline on AWS Teilnahme über Laptop o. PC mit Internetzugang. in - Online-Classroom - | 2.795,00 € zzgl. MwSt. | Buchen | |
29.11.2022 - 02.12.2022 | The Machine Learning Pipeline on AWS Vahrenwalder Straße 156 in 30165 Hannover | 2.795,00 € zzgl. MwSt. | Buchen |
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