Flipboard

MARCH 13, 2023

This post is co-written with Mahima Agarwal, Machine Learning Engineer, and Deepak Mettem, Senior Engineering Manager, at VMware Carbon Black VMware Carbon Black is a renowned security solution offering protection against the full spectrum of modern cyberattacks.

Data Scientist 102

Data Scientist Auto-complete ML Machine Learning 102

AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

Generative AI 87

Generative AI AI Modeling ML AI 87

AWS Machine Learning Blog

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). We provide you with two different solutions for this use case. Both of these solutions allow you to quickly process many millions of pages.

IDP 83

IDP Auto-complete Python Natural Language Processing 83

AWS Machine Learning Blog

AUGUST 3, 2023

Computer vision (CV) is one of the most common applications of machine learning (ML) and deep learning. Use cases range from self-driving cars, content moderation on social media platforms, cancer detection, and automated defect detection. We use deep learning models to solve this problem.

Computer Vision 62

Computer Vision Data Scientist ML Deep Learning 62

Shreyansh Singh

JANUARY 23, 2022

Quite a while back, I had written a post in which I described how to package your Machine Learning models using Docker and deploy them using Flask. The repository also contains the code to train, save and test a simple ML model on the Iris Dataset. streamlit run app.py streamlit run app.py

Machine Learning 64

Machine Learning Automation Python ML 64

AWS Machine Learning Blog

NOVEMBER 30, 2023

Machine learning techniques can help you discover such images. “ Machine learning techniques can help you discover such images. “ The previous post discussed how you can use Amazon machine learning (ML) services to help you find the best images to be placed along an article or TV synopsis without typing in keywords.

Metadata 88

Metadata ML Machine Learning Automation 88

AWS Machine Learning Blog

NOVEMBER 7, 2023

Large language models (LLMs) with their broad knowledge, can generate human-like text on almost any topic. However, their training on massive datasets also limits their usefulness for specialized tasks. Without continued learning, these models remain oblivious to new data and trends that emerge after their initial training.

Large Language Models 89

Large Language Models Generative AI LLM AI 89

AWS Machine Learning Blog

FEBRUARY 20, 2024

In this post, we discuss deploying scalable machine learning (ML) models for diarizing media content using Amazon SageMaker , with a focus on the WhisperX model. This S3 bucket was configured to emit an event when new files are detected within it, triggering an AWS Lambda function.

Metadata 89

Metadata Auto-complete Machine Learning Deep Learning 89

AWS Machine Learning Blog

MAY 25, 2023

Amazon Kendra is a highly accurate and intelligent search service that enables users to search unstructured and structured data using natural language processing (NLP) and advanced search algorithms. Such grouping of similar queries can be done using the concept of semantic similarity.

ML 69

ML Auto-complete NLP Machine Learning 69

AWS Machine Learning Blog

MAY 8, 2023

With Amazon SageMaker , you can manage the whole end-to-end machine learning (ML) lifecycle. It offers many native capabilities to help manage ML workflows aspects, such as experiment tracking, and model governance via the model registry.

Data Science 68

Data Science Machine Learning Python Data Scientist 68

AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. release, AWS customers can now do same things as they could with PyTorch 1.x 24xlarge with AWS PyTorch 2.0

ML 67

ML Deep Learning BERT Python 67

AWS Machine Learning Blog

JULY 18, 2023

Artificial intelligence (AI) and machine learning (ML) have been a focus for Amazon for over 20 years, and many of the capabilities that customers use with Amazon are driven by ML. This blog post introduces a powerful solution for augmenting Amazon Lex with LLM-based FAQ features using the Retrieval Augmented Generation (RAG).

LLM 77

LLM Chatbots Large Language Models Artificial Intelligence 77

AWS Machine Learning Blog

MARCH 13, 2023

Amazon SageMaker Ground Truth Plus is a managed data labeling service that makes it easy to label data for machine learning (ML) applications. One common use case is semantic segmentation, which is a computer vision ML technique that involves assigning class labels to individual pixels in an image.

Machine Learning 66

Machine Learning ML Robotics Software Engineer 66

AWS Machine Learning Blog

AUGUST 29, 2023

In this post, we describe how to create an MLOps workflow for batch inference that automates job scheduling, model monitoring, retraining, and registration, as well as error handling and notification by using Amazon SageMaker , Amazon EventBridge , AWS Lambda , Amazon Simple Notification Service (Amazon SNS), HashiCorp Terraform, and GitLab CI/CD.

Data Scientist 70

Data Scientist Data Quality Python ML 70

The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

MARCH 31, 2023

Intelligent document processing (IDP) with AWS helps automate information extraction from documents of different types and formats, quickly and with high accuracy, without the need for machine learning (ML) skills. For more information, refer to Intelligent document processing with AWS AI services: Part 1.

IDP 64

IDP Natural Language Processing Machine Learning Software Engineer 64

AWS Machine Learning Blog

MARCH 6, 2023

Language models are statistical methods predicting the succession of tokens in sequences, using natural text. Large language models (LLMs) are neural network-based language models with hundreds of millions ( BERT ) to over a trillion parameters ( MiCS ), and whose size makes single-GPU training impractical.

Large Language Models 75

Large Language Models LLM Machine Learning ML 75

AWS Machine Learning Blog

JULY 20, 2023

As AI has evolved, we have seen different types of machine learning (ML) models emerge. One approach, known as ensemble modeling , has been rapidly gaining traction among data scientists and practitioners. In this post, we discuss what ensemble models are and why their usage can be beneficial.

ML 78

ML Python Natural Language Processing Machine Learning 78

AWS Machine Learning Blog

MARCH 2, 2023

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. Hyperparameter optimization is highly computationally demanding for deep learning models.

BERT 73

BERT Deep Learning Metadata Auto-complete 73

The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. It is crucial to save, store, and package these models for their future use and deployment to production. Saving and storing your model the right way takes care of this.

Python 106

Python Metadata ML Deep Learning 106

AWS Machine Learning Blog

MAY 10, 2023

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making inferences on data. SageMaker provides an open-source extension that can be installed on any JupyterLab environment and be used to run notebooks as ephemeral jobs and on a schedule.

Data Scientist 71

Data Scientist Python Software Development Machine Learning 71

The MLOps Blog

DECEMBER 7, 2022

Given that the whole theory of machine learning assumes today will behave at least somewhat like yesterday, what can algorithms and models do for you in such a chaotic context ? There’s an old saying in Argentina that goes: “A río revuelto, ganancia de pescadores”. And that includes data. With that out of the way, let’s dig in!

ML 52

ML ETL Data Scientist Automation 52

The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah. Thanks for having me.

ML 52

ML Data Scientist Software Engineer Machine Learning 52