Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 48000 Hz, 2ch | Size: 2.91 GBGenre: eLearning Video | Duration: 7 hours 30 mins | Language: English

Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using 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 eeering 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 Eeering 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 SageMaker.

Deploy a Sennt 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 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

gfxtra__UDACITY__M.part1.rar.html

gfxtra__UDACITY__M.part2.rar.html

gfxtra__UDACITY__M.part3.rar.html