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Building Code-Free GenerativeAI Apps with PartyRock

2023-12-05T00:19:12+00:00

What is PartyRock? It has been two weeks since Amazon announced PartyRock, an Amazon Bedrock Playground. It comes with the tagline “Everyone can build AI apps”. According to Amazon President and CEO, Andy Jassy, it was just an internal tool created by AWS developers to experiment with Foundation Models from Amazon Bedrock. The name PartyRock was in reference to it being a fun and collaborative way to experience Amazon Bedrock. I joined the party and played around with PartyRock to see what all the fuss was about, and it literally took me less than five minutes to create my first [...]

Building Code-Free GenerativeAI Apps with PartyRock2023-12-05T00:19:12+00:00

How I Prepared for the AWS Cloud Practitioner CLF-C02 Exam as a Data Scientist

2023-12-03T18:07:52+00:00

In the ever-evolving landscape of technology, the pursuit of knowledge and skills is not just a choice but a necessity, especially for professionals like data scientists. This realization led me to embark on a journey towards achieving the AWS Certified Cloud Practitioner CLF-C02 certification, a decision that not only expanded my technical horizons but also underscored the importance of continuous learning in the tech industry. As a data scientist, my daily encounters with vast datasets and complex algorithms had already established a solid foundation in analytics and machine learning. However, with the increasing integration of cloud technologies in data science, [...]

How I Prepared for the AWS Cloud Practitioner CLF-C02 Exam as a Data Scientist2023-12-03T18:07:52+00:00

Amazon AI Fairness and Explainability with Amazon SageMaker Clarify

2023-12-02T01:24:03+00:00

Introduction In the rapidly evolving domain of machine learning, ensuring fairness and explainability in model predictions has become crucial. With Amazon SageMaker Clarify, these critical aspects are not just an afterthought but integral components of the model development and deployment process. This article delves into the world of SageMaker Clarify, offering a comprehensive guide to its capabilities and practical applications. We commence our journey with a high-level understanding of what SageMaker Clarify is and its importance in the day-to-day tasks of machine learning modeling. Our exploration is anchored in a hands-on example, utilizing a specially crafted dataset that simulates loan [...]

Amazon AI Fairness and Explainability with Amazon SageMaker Clarify2023-12-02T01:24:03+00:00

Personal ML Projects with Amazon SageMaker, Amazon Comprehend, Amazon Forecast and Other ML Services

2023-11-30T04:52:46+00:00

Machine learning and artificial intelligence have been powering many of the technologies we use daily, some of which we may not actively pay attention to, and they have become second nature to us. Suppose we actively look for the presence of ML/AI. In that case, we can find them everywhere: natural language processing in our AI Assistants, recommender engines in e-commerce, social media, and music, and fraud detection in finance, among many other technologies. Although these very powerful models are the ones running the digital world we live in, we can replicate the functionalities of said models for our uses, [...]

Personal ML Projects with Amazon SageMaker, Amazon Comprehend, Amazon Forecast and Other ML Services2023-11-30T04:52:46+00:00

Automating Binary Classification Model Building with Amazon SageMaker Autopilot

2023-11-30T10:07:06+00:00

Introduction In the ever-evolving world of machine learning, binary classification stands out as one of the most fundamental and widely used techniques. At its core, binary classification involves categorizing data into one of two groups based on certain features. This method is crucial in various applications, such as spam detection, medical diagnosis, and customer churn prediction. However, building an effective binary classification model can be a complex and time-consuming process, requiring extensive knowledge in data preprocessing, feature engineering, model selection, and optimization. Enter Amazon SageMaker Autopilot – a powerful service designed to automate the process of building, training, and tuning [...]

Automating Binary Classification Model Building with Amazon SageMaker Autopilot2023-11-30T10:07:06+00:00

Leveraging Amazon CloudFront with S3 and Route 53 for Subdomain Configuration

2023-11-20T06:14:26+00:00

Amazon S3 and Route 53, both provided by AWS, offer a comprehensive solution for managing and deploying web content. Route 53 allows you to create alias records that direct to the website endpoint of your S3 bucket. Meanwhile, Amazon S3 is a robust service for hosting static websites. These services, when used together, provide a powerful toolset for web content management. However, there's a key requirement when using these services together: the bucket name in S3 must be the same as the domain or subdomain hosted on Route 53. This is because when a request comes to Route 53, it [...]

Leveraging Amazon CloudFront with S3 and Route 53 for Subdomain Configuration2023-11-20T06:14:26+00:00

Setting up a Static Website on Amazon S3

2023-11-16T02:07:44+00:00

What is Amazon S3? Amazon S3, a scalable and secure object storage service, offers an efficient and cost-effective way to host static websites. In this article, I will guide you through a step-by-step process of setting up a static website on Amazon S3. Whether you're an experienced developer or a beginner just starting out, this guide will equip you with the knowledge and tools you need to launch your website successfully. So, let's dive right in and start building! Sign in to the AWS Management Console and open the Amazon S3 console. In the Buckets list, choose the name of [...]

Setting up a Static Website on Amazon S32023-11-16T02:07:44+00:00

Serverless Model Deployment in AWS: Streamlining with Lambda, Docker, and S3

2023-11-30T06:08:01+00:00

Welcome back to our series on model deployment in AWS! In the fast-paced world of machine learning and data science, the ability to deploy models efficiently and reliably is crucial. This is where AWS services, with their vast array of tools and capabilities, come into play. In this second installment, we will delve into the potent combination of AWS Lambda and Docker, coupled with the convenience of storing models in S3. This trio offers a scalable, cost-effective, and streamlined solution for deploying machine learning models in a production environment. If you recall, in the first part of our series, we [...]

Serverless Model Deployment in AWS: Streamlining with Lambda, Docker, and S32023-11-30T06:08:01+00:00

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