CI/CD Deployment with AWS SAM using Github Action
Data Science and Machine Learning are surely some fast-moving industries and somewhat need you to study at all times to stay ahead and on top in the industry. But the first step of getting into this area seems dreadfully slow due to widely involved technologies and overwhelming terminologies that scare you out of shit.
AWS lowers the barrier to entry for companies and organizations looking for solutions of leveraging ML capabilities by offerings more than 20 services including low-level service like SageMaker, which helps build and manage infrastructure for developing environments, as well as high-level systems like Rekognition that come with pre-built Machine Learning models for image recognition.
This blog will go through nearly all the Machine Learning services offered by AWS.
Tools
SageMaker
SageMaker is the most important microservices set in AWS. It’s a set of tools for deploying machine learning applications. it streamlines all the Machine Learning tasks that come up from preparing data and building a model to training, and deploying it.
Also, The benefits of SageMaker have to do with all the details of how to stage training tasks and deploy inference tasks across a variety of infrastructures.
SageMaker is so powerful that can not be just compressed into one section to introduce. So, I’m decided to use another article to illustrate it in full detail. Please stay tuned.
Development Tools
The critical blockers for traditional developers to become Cloud practitioners are all kinds of new cloud development patterns, including new Cloud IDE, new backend design patterns, and new operation standards. From that end, AWS provides several development tools to ensure the working environment, and smooth the transition experience. Machine Learning plays a vital role in this task.
Amazon CodeGuru is a developer tool that provides intelligent recommendations to improve code quality and identify an application’s most expensive lines of code. Integrate CodeGuru into your existing software development workflow to automate code reviews during application development and continuously monitor application’s performance in production and provide recommendations and visual clues on how to improve code quality, application performance, and reduce overall cost.
- CodeGuru Reviewer uses machine learning and automated reasoning to identify critical issues, security vulnerabilities, and hard-to-find bugs during application development and provides recommendations to improve code quality.
- CodeGuru Profiler helps developers find an application’s most expensive lines of code by helping them understand the runtime behavior of their applications, identify and remove code inefficiencies, improve performance, and significantly decrease compute costs.
Amazon DevOps Guru is a service powered by machine learning (ML) that is designed to make it easy to improve an application’s operational performance and availability. DevOps Guru helps detect behaviors that deviate from normal operating patterns so you can identify operational issues long before they impact your customers. When DevOps Guru identifies a critical issue, it automatically sends an alert and provides a summary of related anomalies, the likely root cause, and context for when and where the issue occurred.
Tools for Text Mining
Text is important for human society and it is also more difficult and more tricky to process than other standard machine learning tasks like numerical classification. So, AWS provides a wide range of tools for NLP (natural language processing), GLU (natural language understanding), as well as NLG (natural language generation). With all kinds of text mining appliances, you can do sentiment analysis, machine translation, also speech recording. They are also accommodating if you want to build conversational user interfaces or summarize texts.
Amazon Comprehend for natural language processing and text analytics helps you understand text sentiment and relate texts to each other.
Amazon Lex is a service for building conversational interfaces using voice and text. With Lex, you can use the same deep learning engine that powers Alexa in your own applications.
Amazon Textract extracts text and data from scanned documents. It’s not just OCR but backed by Machine Learning models that have analyzed many types of documents, and can identify the contents of fields in forms and information stored in tables.
Amazon Transcribe could be used to turn any speech recording into a text. If you need to go the other way around, Amazon Polly will synthesize lifelike speech from any text.
Amazon Translate caters to your multilingual needs by translating every text into the language of your choice.
Amazon Polly is a service that turns text into lifelike speech. Polly lets you create applications that talk, enabling you to build entirely new categories of speech-enabled products. Polly is an Amazon artificial intelligence (AI) service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice.
Tools for Image and Video
The ability to verify, organize, analysis millions and tons of images will unlock a whole new set of possibilities.
Amazon Rekognition offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos. From face detection to text extraction.
AWS Panorama is a machine learning (ML) appliance and software development kit (SDK) that brings CV to on-premises internet protocol (IP) cameras.
Manufacturing Capabilities
Amazon Lookout for Vision is a machine learning (ML) service that spots defects and anomalies in visual representations using computer vision (CV). With Amazon Lookout for Vision, manufacturing companies can increase quality and reduce operational costs by quickly identifying differences in images of objects at scale.
Amazon Lookout for Equipment analyzes the data from the sensors on your equipment (e.g. pressure in a generator, flow rate of a compressor, revolutions per minute of fans), to automatically train a machine learning model based on just your data, for your equipment – with no ML expertise required.
Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies in business and operational data, such as a sudden dip in sales revenue or customer acquisition rates.
Amazon Monitron is an end-to-end system that uses machine learning (ML) to detect abnormal behavior in industrial machinery, enabling you to implement predictive maintenance and reduce unplanned downtime.
Tools for Low Level Scientific Environment
TensorFlow is one of many deep learning frameworks available to researchers and developers to enhance their applications with machine learning. AWS provides broad support for TensorFlow, enabling customers to develop and serve their own models across computer vision, natural language processing, speech translation, and more.
Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch, and ONNX models.
AWS Inferentia is a machine learning inference chip designed to deliver high performance at low cost. AWS Inferentia will support the TensorFlow, Apache MXNet, and PyTorch deep learning frameworks, as well as models that use the ONNX format.
Other Tools
Amazon Augmented AI (Amazon A2I) is a machine learning service that makes it easy to build the workflows required for human review.
Amazon Fraud Detector is a fully managed service that uses machine learning (ML) and more than 20 years of fraud detection expertise from Amazon, to identify potentially fraudulent activity so customers can catch more online fraud faster.
Amazon HealthLake is a HIPAA-eligible service that healthcare providers, health insurance companies, and pharmaceutical companies can use to store, transform, query, and analyze large-scale health data.
Amazon Kendra is an intelligent search service powered by machine learning. Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they are looking for, even when it’s scattered across multiple locations and content repositories within your organization.
Amazon Personalize is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.
Amazon Personalize is like having your own Amazon.com machine learning personalization team at your disposal, 24 hours a day.
AWS DeepRacer is a 1/18th scale race car which gives you an interesting and fun way to get started with reinforcement learning (RL). RL is an advanced machine learning (ML) technique which takes a very different approach to training models than other machine learning methods.
References
- Summary
Amazon SageMaker
Serverless
CI/CD Deployment with AWS SAM using Github Action
http://vincentgaohj.github.io/Blog/2022/02/16/CICD-Deployment-with-AWS-SAM-using-Github-Action/
