Edward HuforVext Blogblog.vextapp.com·Apr 11, 2024Vext v1.7: Bring Your Own AWS SageMaker LLM, Mistral Large, and Template GalleryWe've been listening to your feedback, rolling up our sleeves, and, after much anticipation, are thrilled to introduce Vext v1.7. This update is all about empowering you, the developers, with even more flexibility, inspiration, and power at your fing...Discuss·57 readsllm
Sumit Mondalsumit007.hashnode.dev·Feb 11, 2024AWS Healthomics: Navigating Your Health Data in the CloudIntroduction: In the dynamic world of cloud computing, Amazon Web Services (AWS) continues to lead the way with innovative solutions. One such cutting-edge service is AWS Healthomics, designed to empower healthcare organizations by efficiently managi...DiscussAWS - HandsOn#AWSHealthomics
Timur Galeevtgaleev.com·Jan 22, 2024Beginning the Journey into ML, AI and GenAI on AWSMachine Learning (ML), Artificial Intelligence (AI), and Generative Artificial Intelligence (GenAI) are transformative technologies that have the potential to revolutionize industries across the globe. At the last AWS re:Invent, there were numerous u...Discuss·1 like·95 readsFMs
Denny Wangdenny.hashnode.dev·Jan 15, 2024Efficient Machine Learning Deployment: Using Hugging Face with AWS SageMaker EndpointsWelcome back to our ongoing exploration of advanced NLP techniques using Hugging Face and AWS SageMaker. In our previous discussions, we delved into running NLP models in SageMaker notebook instances. Today, we're taking a step further — deploying th...Discusssagemaker
Denny Wangdenny.hashnode.dev·Jan 15, 2024Leveraging Hugging Face and AWS SageMaker: Streamlining Advanced NLP Tasks"What is Hugging Face? Hugging Face is a company known for its Transformers library, which has revolutionized the way we use and implement natural language processing (NLP) models. It offers an extensive collection of pre-trained models that cover a w...DiscussAI
DataOps Labsblog.dataopslabs.com·Dec 19, 2023Adaptive Fraud Detection System Leveraging AWS BedrockIntroduction Fraudulent activities pose a significant threat to businesses and individuals alike, with increasingly sophisticated methods being employed by fraudsters. Traditional fraud detection systems often struggle to keep up with evolving fraud ...Discuss·54 readsAWS Bedrock Learning SeriesAWS
Sumit Mondalsumit007.hashnode.dev·Dec 3, 2023Unleashing the Power of AWS: A Creative Journey into Machine Learning with SageMakerIntroduction: In the vast landscape of cloud computing, Amazon Web Services (AWS) stands tall as a pioneer, offering a myriad of services that empower businesses to innovate and thrive in the digital era. One such groundbreaking offering is Amazon Sa...DiscussAWS - Theorysagemaker
DataChefforDataChef's Blogblog.datachef.co·Nov 12, 2023No Code, All Insight: SageMaker Canvas Connects Data Analysts to Machine LearningWhat is No-Code ML? As a data scientist, I was always skeptical of no-code solutions since they usually provide so little flexibility that makes them practically useless or tries to provide too much flexibility that makes their UI/UX impossible to na...Discuss·57 readsMachine Learning
Vineethkumar Marpadge ☁️ vmarpadge.hashnode.dev·Sep 13, 2023Unlocking the Power of CodeWhisperer in Your SageMaker Notebook: A Step-by-Step Guide.In the world of data science and machine learning, having a seamless and efficient development environment is crucial. Amazon SageMaker has been a go-to platform for many data professionals, providing a collaborative space to build, train, and deploy...DiscussAWS
Stephen OladeleforAI Community Africa ("AI School Africa")fearless-goat-measure-54.hashnode.dev·Jun 25, 2023Spark Machine Learning Pipelines: Make Real-Time ML Possible with MLeap on AWSIf you have used Apache Spark for machine learning, one challenge you may have faced is that the current ecosystem is optimized for batch inference workloads, not real-time inference processing. This can be a bummer if your use case requires low-late...Discuss·18 likes·110 readsBuilding Real-Time Machine Learning Pipelines with Apache Spark and MLeaprealtime