Deploy your first CloudFormation Script

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Infrastructure as Code (IaC) is a key DevOps concept that is essential in the Data Science world when we’re building and defining production level workloads. IaC allows developers to manage a project’s infrastructure as software. This enables developers to easily maintain and configure changes within a project’s resources and architecture. While similar to traditional scripting, IaC allows for developers to use declarative language to provision resources. There’s numerous IaC tools that are available such as Terraform, Chef, Puppet, and Ansible. For today’s demonstration we’ll be using CloudFormation which is specific for AWS resources. Through the article you will understand how…


Use AWS Rekognition to build Computer Vision Projects in under 50 Lines of Python Code

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Computer Vision (CV) can be a very theory heavy and intense field with a lot of ML and Mathematical knowledge required to unpack and understand the algorithms that power topics such as Object Detection, Facial Recognition, and Object Tracking. If you don’t have the requisite experience theoretically or don’t have the time to build a custom ML/CV model, AWS Rekognition enables you to build powerful CV applications through API calls. AWS Rekognition is one of many Auto-AI services offered by AWS. These services are meant for developers who don’t have much of a background in ML, or Data Scientists low…


Notes from Industry

Load Testing a Flask ML Application using Locust

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As I continue to navigate the world of Data Science, ML, AI, whatever you want to call it I continue to find more and more terms that I used to initially be afraid of diving into. As I documented in a previous article of mine, I come from a non-technical background and often swept key software terms such as “Testing” right under the mat. After gaining more experience in building applications powered by ML I understood the necessity of a particular form of testing called load testing, also known as performance testing. Load testing is a manner in which you…


CLI examples and use cases to create more efficient Machine Learning workflows

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When first learning Data Science, I did not place a heavy emphasis on understanding terms such as Unix/Linux and Bash. Coming from a non-Computer Science background it seemed quite alien and hard to understand, but I quickly came to realize how essential the Command Line Interface (CLI) is in managing your Data Science workloads. To become a strong Data Scientist/MLE or just work with software in general you need to be able to navigate and work with the CLI on your machine with ease. There’s so many use cases within Data Science for using the CLI outside of the comfortable…


Working with AWS S3 using the Node.js SDK

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While working within the Management Console can be a good way to get started in your AWS learning journey, it is essential and convenient for a developer to start working with AWS services and resources in a programmatic fashion.

You can interact with services through the AWS CLI or the SDK. For this article, we will be covering the Node.js SDK that AWS offers for developers to work with their resources in the cloud. We will work with the SDK to interact with a core AWS service in AWS S3. …


Demo of using AWS Amplify to power your application with ML/AI

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Amazon Web Services (AWS) is constantly expanding its offerings in various domains such as application development, Machine Learning/AI, and IoT. Some of its services even offer a fusion of the different domains at a higher level. AWS Amplify is a service that offers the capability to build mobile/web applications with popular frameworks such as React. Recently Amplify integrated various high-level ML services such as Transcribe, Translate, Comprehend, and Rekognition that enable developers to easily power their applications with AI. …


Common feature engineering/EDA tasks, compiled

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The longest part of any data analysis/science task is preparing and configuring your data properly. A model only performs as well as the data that it is fed and there’s a lot of transformations that the data may have to undergo to be ready for model training. Over the years I have compiled a Notion page that highlights many of the common tasks Data Scientists need to perform for data preparation. I’ve listed a few of the examples below, but the entirety of the examples can be found in the following link. …


Tips/Resources for making the career change in your Undergraduate

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After spending two years as a pre-medical student at the University of Virginia I slowly realized I could not and did not want to sustain the level of dedication and time required for the next 10 years of my life (I was on pace for a lot of gap years lol). I transitioned slowly into a Statistics major and decided I was interested in a career track called “Data Science”. I didn’t really know what the track entailed nor what it even meant, I just heard the words being thrown around a lot as the new lucrative job of the…


For those struggling with stress after graduation, you’re not alone

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I recently had my graduation ceremony for the University of Virginia (UVA) this past weekend, commencing what’s been the best four years of my life. Countless nights out, classes skipped, and crazy times/memories with people who evolved from strangers to life-long friends and family. It’s been a whirlpool of emotions ranging from nostalgia to fear as the reality of adulthood hits. No longer do we have the freedom to skip class, change majors, and in general just mess up while enjoying the benefits of our youth. I felt lost as I couldn’t fathom how quickly these years have flown by…


Building a web application for Medical Entity Detection using AWS Comprehend

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Named Entity Recognition (NER) is one of the most popular and in-demand NLP tasks. As NER has expanded it has become more domain specific as well. Building custom NER models for a specific domain such as healthcare/medical, can be difficult and require extensive amounts of data and computing power. AWS Comprehend is a high-level service, AWS offers that automates many different NLP tasks such as Sentiment Analysis, Topic Modeling, and NER. Comprehend branched out to create an sub-service called Comprehend Medical, that is specifically geared for Medical NER. In this article we will cover how to build a web application…

Ram Vegiraju

Incoming Solutions Architect @ Amazon. Passionate about Data Science/ML. https://ramvegiraju.github.io/PersonalPortfolio/

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