Udacity | Machine Learning Engineer Nanodegree v4.0.0 [FCO]
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size2.9 GB
- Uploaded BySunRiseZone
- Downloads275
- Last checkedJul. 27th '20
- Date uploadedJul. 25th '20
- Seeders 59
- Leechers33
Infohash : 0267528BFB7734DB0CAA39CC506D9D87C46BEF6A
Lynda and other Courses >>> https://www.freecoursesonline.me/
For Developer Tools & Apps >>> https://ftuapps.com/
Forum for discussion >>> https://1hack.us/
Nanodegree Program–nd009t
Publisher : Udacity
Subtitle : English CC Included
Updated : July 2020
Course Source : https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t
Become a Machine Learning Engineer
Learn advanced machine learning techniques and algorithms -- including how to package and deploy your models to a production environment.
ESTIMATED TIME
- 3 Months
- At 10 hrs/week
PREREQUISITES
- Intermediate Python & Machine Learning Algorithms
IN COLLABORATION WITH
What You Will Learn
Machine Learning Engineer
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.
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
Learn with the best
Cezanne Camacho, Mat Leonard, Luis Serrano, Dan Romuald Mbanga, Jennifer Staab, Sean Carrell, Josh Bernhard, Jay Alammar, Andrew Paster
GET STARTED WITH
Machine Learning Engineer
LEARN
• Learn advanced machine learning techniques and algorithms, including deployment to a production environment.
AVERAGE TIME
• On average, successful students take 3 months to complete this program.
BENEFITS INCLUDE
• Real-world projects from industry experts
• Technical mentor support
• Personal career coach & career services
STAY SHARP WHILE STAYING IN
• Financial support available worldwide to help in this challenging time
• Spend your time at home learning new, higher-paying job skills
• Commit to a brighter future by learning today
Why should I enroll?
As more and more companies are looking to build machine learning products, there is a growing demand for engineers who are able to deploy machine learning models to global audiences. In this program, you’ll learn how to create an end-to-end machine learning product. You’ll deploy machine learning models to a production environment, such as a web application, and evaluate and update that model according to performance metrics. This program is designed to give you the advanced skills you need to become a machine learning engineer.
Read more at course page.
Files:
Code:
- udp://opentor.org:2710/announce
- udp://p4p.arenabg.com:1337/announce
- udp://tracker.torrent.eu.org:451/announce
- udp://tracker.cyberia.is:6969/announce
- udp://9.rarbg.to:2710/announce
- udp://exodus.desync.com:6969/announce
- udp://explodie.org:6969/announce
- udp://tracker.moeking.me:6969/announce
- udp://tracker.opentrackr.org:1337/announce
- udp://tracker.tiny-vps.com:6969/announce
- udp://ipv4.tracker.harry.lu:80/announce
- udp://tracker.coppersurfer.tk:6969/announce
- udp://tracker.leechers-paradise.org:6969/announce
- udp://open.stealth.si:80/announce
- udp://tracker.iamhansen.xyz:2000/announce