AWS Certified Machine Learning Specialty (MLS-C01)

• 0
• 1
• 2
• 3
• 4
• 5

How to detect a biased solution, ensure model fairness and prove the fairness

New Endpoint focused section on how to make SageMaker Endpoint Changes with Zero Down

Lab notebook now use spot-training as the default option. Save over 60% in training costs

NEW: Nuts and Bolts of Optimization, quizzes

All code examples and Labs were updated to use version 2.x of the SageMaker Python SDK

Anomaly Detection with Random Cut Forest - Learn the intuition behind anomaly detection using Random Cut Forest. With labs.

Bring Your Own Algorithm - We take a behind the scene look at the SageMaker Training and Hosting Infrastructure for your own algorithms. With Labs

d Practice Test and additional lectures for Exam Preparation added

Welcome to AWS Machine Learning Specialty Course!

I am Chandra Lingam, and I am your instructor

In this course, you will gain first-hand SageMaker experience with many hands-on labs that demonstrates specific concepts

We start with how to set up your SageMaker environment

If you are new to ML, you will learn how to handle mixed data types, missing data, and how to verify the quality of the model

These topics are very important for an ML practitioner as well as for the certification exam

SageMaker uses containers to wrap your favorite algorithms and frameworks such as Pytorch, and TensorFlow

The advantage of a container-based approach is it provides a standard interface to build and deploy your models

It is also straightforward to convert your model into a production application

In a series of concise labs, you will in fact train, deploy, and invoke your first SageMaker model

Like any other software project, ML Solution also requires continuous improvement

We look at how to safely incorporate new changes in a production system, perform A/B testing, and even rollback changes when necessary

All with zero down to your application

We then look at emeg social trends on the fairness of Machine learning and AI systems.

What will you do if your users accuse your model as racially biased or gender-biased How will you handle it

In this section, we look at the concept of fairness, how to explain a decision made by the model, different types of bias, and how to measure them

We then look at Cloud security – how to protect your data and model from unauthorized use

You will also learn about recommender systems to incorporate features such as movie and product recommendation

The algorithms that you learn in the course are state of the art, and tuning them for your dataset is especially challeg

So, we look at how to tune your model with automated tools

You will gain experience in series forecasting

Anomaly detection and building custom deep learning models

With the knowledge, you gain here and the included high-quality practice exam, you will easily achieve the certification!

And something unique that I offer my students is a weekly study group meeting to discuss and clarify any questions

I am looking forward to seeing you!

Thank you!

Who this course is for
This course is designed for anyone who is interested in AWS cloud based machine learning and data science
AWS Certified Machine Learning - Specialty Preparation

HomePage:

https://anonymz.com/https://www.udemy.com/course/aws-machine-learning-a-complete-guide-with-python/

DOWNLOAD
uploadgig.com


rapidgator.net


nitro.download

---

Related News

AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 1 Data Engineering
AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 1 Data Engineering Released 2/2023... AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 2 Exploratory Data Analysis
AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 2 Exploratory Data Analysis... Learn Data Mining & Machine Learning with Python
Learn Data Mining & Machine Learning with Python Genre: eLearning | MP4 | Video: h264,... Cloud Academy - Building a Machine Learning Model
Cloud Academy - Building a Machine Learning Model Released 3/2023 MP4 | Video: h264, 1920x1080 |...

System Comment

Facebook Comment