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AWS SageMaker, Machine Learning and AI with Python [Video]

More Information
Learn
  • Learn the AWS Machine Learning algorithms, Predictive quality assessment, Model optimization
  • Integrate predictive models with your application using simple and secure APIs
  • Convert your ideas into highly scalable products in days
About

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

Style and Approach

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 a variety of AWS provided capabilities including Cognito.

Features

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 knobs are essential to tweak 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 the integration of machine learning models with your application. You will walk through several integration and security options.
Course Length 12 hours 58 minutes
ISBN9781789535976
Date Of Publication 17 Jul 2018

Authors

Chandra Lingam

Chandra Lingam spent 15 years at Intel, developing and managing systems that handled hundreds of terabytes of worldwide factory data. Chandra is an expert on Amazon Web Services, mission critical systems and machine learning. He has a rich background in systems' development in both traditional IT data centers and Cloud-based infrastructures. For those new to AWS, he is uniquely positioned to guide you to become an expert in AWS Cloud platform.He has a Master's degree in Computer Science from ASU and Bachelor's degree in Computer Science from Thiagarajar College of Engineering, Madurai.