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Machine Learning Mathematics: Regression Basics

2024-01-28T03:02:56+00:00

In recent years, of the ever-evolving landscape of technology, a few of the most prominent buzzwords that continue to capture the imagination of innovators and entrepreneurs alike are Machine Learning (ML) and Artificial Intelligence (AI). With the boom of OpenAI’s ChatGPT last November 2023, as well as the many that followed suit, including major tech companies like Meta with their LLaMa model and Google’s PaLM and newly announced Gemini, ML and AI will most likely be the spotlight for the months, years, and possibly, decades to come.  In a previous article, The AI Revolution: An Overview of Generative AI and [...]

Machine Learning Mathematics: Regression Basics2024-01-28T03:02:56+00:00

Release with a Pipeline: Continuous Delivery to AWS with GitHub Actions

2024-01-24T01:07:44+00:00

This is the final part of a three-part article about a Web Application Project from building a private infrastructure to building a deployment pipeline using AWS’ cloud-native continuous delivery service AWS CodePipeline, and now finalizing the infrastructure to be accessible in a public domain and building a pipeline for continuous deployment using a third-party CD tool – GitHub Actions. From the private infrastructure previously built, we will update the S3 policy to add a statement for an allowed action for the CloudFront resource. As best practice, this statement will be added to the Terraform script of the infrastructure to make it [...]

Release with a Pipeline: Continuous Delivery to AWS with GitHub Actions2024-01-24T01:07:44+00:00

Distributed Data Parallel Training with TensorFlow and Amazon SageMaker Distributed Training Library

2024-01-22T00:58:08+00:00

Introduction In the realm of machine learning, the ability to train models effectively and efficiently stands as a cornerstone of success. As datasets grow exponentially and models become more complex, traditional single-node training methods increasingly fall short. This is where distributed training enters the picture, offering a scalable solution to this growing challenge. Distributed Training Overview Distributed training is a technique used to train machine learning models on large datasets more efficiently. By splitting the workload across multiple compute nodes, it significantly reduces training time. There are two main strategies in distributed training: data parallelism, where the dataset is partitioned [...]

Distributed Data Parallel Training with TensorFlow and Amazon SageMaker Distributed Training Library2024-01-22T00:58:08+00:00

Securing Machine Learning Pipelines: Best Practices in Amazon SageMaker

2024-01-17T00:45:41+00:00

Introduction In today's digital era, the importance of security in machine learning (ML) pipelines cannot be overstated. As ML systems increasingly become integral to business operations and decision-making, ensuring the integrity and security of these systems is paramount. A breach or a flaw in an ML pipeline can lead to compromised data, erroneous decision-making, and potentially catastrophic consequences for businesses and individuals alike. This section will delve into why securing ML pipelines is crucial, highlighting the potential risks and impacts of security lapses. Short Introduction to Amazon SageMaker Amazon SageMaker is a fully managed service that provides every developer and [...]

Securing Machine Learning Pipelines: Best Practices in Amazon SageMaker2024-01-17T00:45:41+00:00

Building a Deployment Pipeline for a React Application with AWS CodePipeline

2024-01-07T02:48:10+00:00

This is the second part of a series of blogs about the platform management of a React Application infrastructure by adding a continuous deployment component to the earlier infrastructure. In an earlier article, I wrote about how a private react application infrastructure can be deployed with Terraform code. Now, we will explore this further by building a deployment pipeline using AWS CodePipeline. Let's assume that the source code of the React web application is hosted on GitHub. Using the GitHub connections feature of AWS CodePipeline, we can authorize the third-party provider to work with AWS resources to establish integration between [...]

Building a Deployment Pipeline for a React Application with AWS CodePipeline2024-01-07T02:48:10+00:00

Securing LLMs with Guardrails for Amazon Bedrock

2024-01-03T00:32:13+00:00

One of the pillars of the AWS Well-Architected Framework is security. It is a foundational concept when running your workloads in the cloud to think about privacy, access limits, compliance with regulatory requirements, and data protection; and this includes Amazon Bedrock. Along with several AI announcements during the keynote of AWS CEO, Adam Selipsky during AWS re:Invent 2023 was Guardrails for Amazon Bedrock. As AI technology evolves and becomes more mature, it makes sense to also reinvent the way usage is handled by security safeguards. Guardrails for Amazon Bedrock allow security policies to be applied across foundational models, to fulfill [...]

Securing LLMs with Guardrails for Amazon Bedrock2024-01-03T00:32:13+00:00

How to Install and Configure PHP OpCache with Web Viewer on Ubuntu 20.04

2024-01-02T01:18:27+00:00

The performance of your PHP applications can be significantly enhanced by using OpCache, a PHP opcode cache. OpCache reduces the need to recompile your PHP scripts on each request by storing the generated bytecode in memory, resulting in quicker execution rates and lessened server load. Image retrieved from https://www.pinterest.ph/pin/flash-running-poster-custom-posters-design-your-own-wall-art-create-personalized-prints--792281759458556733/ This article will walk you through installing and configuring PHP OpCache with Web Viewer on Ubuntu 20.04. Install OpCache Install the Nginx, PHP, and additional PHP extensions with the following command: sudo -i apt-get install nginx php php-fpm php-cli php-OpCache php-mysql php-zip php-gd php-mbstring php-curl php-xml -y After installing, use [...]

How to Install and Configure PHP OpCache with Web Viewer on Ubuntu 20.042024-01-02T01:18:27+00:00

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