AWS Machine Learning: A Complete Guide With Python هذه الدورة تدرس باللغة الإنجليزية

تفاصيل الدورة

*** NEW PREVIEW VIDEOS: Take a look at several newly enabled Preview videos. All lectures in Section 3 and Section 4 on Linear Regression are available for preview as well as Section 15 Integration objectives 

Note: AWS Machine Learning is not part of free-tier.  So, you will incur a small charge when creating and running prediction on models. For this course, I spent USD 5-6 total for creating and testing all models. ***

This course is designed to make you an expert in AWS Machine Learning and it teaches you how to convert your cool ideas into highly scalable products in a matter of days.

Biggest challenge for a Data Science professional is how to convert the proof-of-concept models into actual products that your customers can use. There are several courses on machine learning that teach you how to build models in R, Python, Matlab and so forth.  However, converting a model into a scalable solution and integrating with your existing application requires a lot of effort and development.  The real success of your ideas and concepts depends on how soon you can put the capabilities in the hands of your customers.

With AWS Machine Learning service, you can easily conduct experiments and test your concepts. Once you are happy, you can instantly scale to support millions of requests. No separate development work needed.

This course is focused on three aspects:

The Core of the machine learning process is the algorithm itself.  Gaining an intuitive understanding of the algorithm, how does it find the solution, and what are the knobs to tweak is essential for a successful career in this field.  That is where we will focus first.

Once we build the model, how do we know if it is good or bad? Or If we want to compare two different models, how do we decide which one to pick?  We will look at industry standard metrics and powerful visualization tools that AWS provides to assess the goodness of a model.

The third aspect and most exciting part of model development is putting the prediction capability in the hands of the users, validate how they are using it and identify what needs to be refined.  There is a whole section in this course dedicated to integration of machine learning models with your application.  We will walk thru several integration and security options.

This course is completely hands-on with examples using: AWS Web Console, Python Notebook Files, and Web clients built on AngularJS. You will also learn and integrate security into exercises using variety of AWS provided capabilities including Cognito.

There are Quizzes and supporting resources as well.