Description
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.
This program is intended for students who already have knowledge of machine learning algorithms.
Learn advanced machine learning deployment techniques and software engineering best practices.
3 months to complete
Prerequisite Knowledge
To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and intermediate knowledge of machine learning algorithms.
Software Engineering Fundamentals
In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.
- Build a Python Package
- Machine Learning in Production
- Learn how to deploy machine learning models to a production environment using Amazon SageMaker.
- Deploy a Sentiment Analysis Model
- Machine Learning Case Studies
Apply machine learning techniques to solve real-world tasks; explore data and deploy both built-in and custom-made Amazon SageMaker models.
- Plagiarism Detector
- Machine Learning Capstone
- In this capstone lesson, you’ll select a machine learning challenge and propose a possible solution.
- Capstone Proposal and Project
Download Links
Direct Download
Machine Learning Engineer Nanodegree v4.0.zip (2.8 GB) | Mirror
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