AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

ML 124

ML ML AWS SQL 124

Hacker News

OCTOBER 15, 2024

Over the course of 2023, we rapidly scaled up our training clusters from 1K, 2K, 4K, to eventually 16K GPUs to support our AI workloads. Today, we’re training our models on two 24K-GPU clusters. We don’t expect this upward trajectory for AI clusters to slow down any time soon. Building AI clusters requires more than just GPUs.

Clustering 180

Clustering AI AI Deep Learning 180

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

AWS 123

AWS Machine Learning Machine Learning ML 123

AWS Machine Learning Blog

MARCH 11, 2025

simple Finance Did meta have any mergers or acquisitions in 2022? The implementation included a provisioned three-node sharded OpenSearch Service cluster. About the author Prasanna Sridharan is a Principal Gen AI/ML Architect at AWS, specializing in designing and implementing AI/ML and Generative AI solutions for enterprise customers.

K-nearest Neighbors 97

K-nearest Neighbors AWS Database AI 97

IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

AWS Machine Learning Blog

MAY 31, 2023

Running machine learning (ML) workloads with containers is becoming a common practice. What you get is an ML development environment that is consistent and portable. With containers, scaling on a cluster becomes much easier. With containers, scaling on a cluster becomes much easier. Run the ML task on Amazon ECS.

AWS 106

AWS Machine Learning Machine Learning ML 106

Google Research AI blog

FEBRUARY 28, 2023

Adherence to such public health programs is a prevalent challenge, so researchers from Google Research and the Indian Institute of Technology, Madras worked with ARMMAN to design an ML system that alerts healthcare providers about participants at risk of dropping out of the health information program. certainty when used correctly.

ML 72

ML ML Deep Learning Deep Learning 72

Flipboard

FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. We use Slurm as the cluster management and job scheduling system.

Clustering 132

Clustering AWS Deep Learning Deep Learning 132

AWS Machine Learning Blog

FEBRUARY 7, 2025

This post, part of the Governing the ML lifecycle at scale series ( Part 1 , Part 2 , Part 3 ), explains how to set up and govern a multi-account ML platform that addresses these challenges. An enterprise might have the following roles involved in the ML lifecycles. This ML platform provides several key benefits.

ML 63

ML ML Data Scientist AWS 63

ODSC - Open Data Science

MAY 30, 2023

Be sure to check out his talk, “ ML Applications in Asset Allocation and Portfolio Management ,” there! The year 2022 presented two significant turnarounds for tech: the first one is the immediate public visibility of generative AI due to ChatGPT. Editor’s note: Peter Schwendner, PhD is a speaker for ODSC Europe this June.

ML 52

ML ML Machine Learning Machine Learning 52

Applied Data Science

AUGUST 2, 2021

Big Ideas What to look out for in 2022 1. They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Give this technique a try to take your team’s ML modelling to the next level.

Data Science 130

Data Science Data Scientist ML ML 130

AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. Then we needed to Dockerize the application, write a deployment YAML file, deploy the gRPC server to our Kubernetes cluster, and make sure it’s reliable and auto scalable. We recently developed four more new models.

ML 97

ML ML Deep Learning Deep Learning 97

Mlearning.ai

AUGUST 7, 2023

Enterprises, research and development teams shared GPU clusters for this purpose. on the clusters to get the jobs and allocate GPUs, CPUs, and system memory to the submitted tasks by different users. The authors of [1] propose a resource-sensitive scheduler for shared GPU cluster. SLURM, LFS, Kubernetes, Apache YARN, etc.)

Clustering 52

Clustering Deep Learning Deep Learning Algorithm 52

AWS Machine Learning Blog

SEPTEMBER 12, 2024

Thomson Reuters , a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. LLMs disrupt the industry Towards the end of 2022, groundbreaking LLMs were released that realized drastic improvements over previous model capabilities.

Clustering 105

Clustering AWS ML ML 105

AWS Machine Learning Blog

JUNE 7, 2023

Starting June 7th, both Falcon LLMs will also be available in Amazon SageMaker JumpStart, SageMaker’s machine learning (ML) hub that offers pre-trained models, built-in algorithms, and pre-built solution templates to help you quickly get started with ML. In 2022, Hoffman et al. In 2022, Hoffman et al.

Clustering 101

Clustering Machine Learning Machine Learning AWS 101

AWS Machine Learning Blog

MARCH 6, 2023

These factors require training an LLM over large clusters of accelerated machine learning (ML) instances. SageMaker Training is a managed batch ML compute service that reduces the time and cost to train and tune models at scale without the need to manage infrastructure. SageMaker-managed clusters of ml.p4d.24xlarge

AWS 105

AWS Clustering ML ML 105

ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. NLP Cloud Platforms Cloud-based services are the norm in 2022, this leads to a few service providers becoming increasingly popular.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

Snorkel AI

MARCH 30, 2023

Rapid, model-guided iteration with New Studio for all core ML tasks. Enhanced studio experience for all core ML tasks. Snorkel introduced Data-centric Foundation Model Development capabilities in November 2022 for enterprises to overcome these challenges and leverage foundation models in production. PDF extraction improvements.

ML 98

ML ML Supervised Learning Azure 98

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

SQL 52

SQL ML ML Python 52

AWS Machine Learning Blog

JANUARY 30, 2023

Amazon SageMaker provides a suite of built-in algorithms , pre-trained models , and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning.

Algorithm 103

Algorithm Clustering Machine Learning Machine Learning 103

AWS Machine Learning Blog

APRIL 12, 2023

This step-function instantiated a cluster of instances to extract and process data from S3 and the further steps of pre-processing, training, evaluation would run on a single large EC2 instance. This became a bottleneck in troubleshooting, adding, or removing a step, or even in making some small changes in the overall infrastructure.

ML 107

ML ML AWS Deep Learning 107

Flipboard

FEBRUARY 7, 2025

For more information, see Creating connectors for third-party ML platforms. Create an OpenSearch model When you work with machine learning (ML) models, in OpenSearch, you use OpenSearchs ml-commons plugin to create a model. You created an OpenSearch ML model group and model that you can use to create ingest and search pipelines.

Database 86

Database AWS Python ML 86

AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

ML 91

ML ML Machine Learning Machine Learning 91

ODSC - Open Data Science

JUNE 6, 2023

October 2022). Spark provides this abstraction layer to make it easy for a data engineer to pass this interface to an ML engineer to implement. This function makes it easy to define custom aggregation functions in Python. When combined with event-time windows, analyzing the embeddings in real-time becomes much more feasible.

Machine Learning 90

Machine Learning Machine Learning Data Science Clustering 90

Defined.ai blog

OCTOBER 9, 2022

Fight sophisticated cyber attacks with AI and ML When “virtual” became the standard medium in early 2020 for business communications from board meetings to office happy hours, companies like Zoom found themselves hot in demand. There is also concern that attackers are using AI and ML technology to launch smarter, more advanced attacks.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence ML ML 52

AWS Machine Learning Blog

NOVEMBER 16, 2023

Photo by Scott Webb on Unsplash Determining the value of housing is a classic example of using machine learning (ML). Almost 50 years later, the estimation of housing prices has become an important teaching tool for students and professionals interested in using data and ML in business decision-making. and 5.498, respectively.

ML 113

ML ML AWS Machine Learning 113

Pickl AI

NOVEMBER 28, 2024

Introduction Machine Learning ( ML ) is revolutionising industries, from healthcare and finance to retail and manufacturing. As businesses increasingly rely on ML to gain insights and improve decision-making, the demand for skilled professionals surges. billion in 2022 and is expected to grow to USD 505.42

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

JANUARY 13, 2023

It involves training a global machine learning (ML) model from distributed health data held locally at different sites. The eICU data is ideal for developing ML algorithms, decision support tools, and advancing clinical research. Training ML models with a single data point at a time is tedious and time-consuming.

AWS 96

AWS Analytics Analytics Machine Learning 96

Pickl AI

NOVEMBER 4, 2024

in 2022, according to the PYPL Index. Scikit-learn covers various classification , regression , clustering , and dimensionality reduction algorithms. Python’s rich ecosystem offers several libraries, such as Scikit-learn and TensorFlow, which simplify the implementation of ML algorithms.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 3, 2023

We analyzed around 215 matches from the Bundesliga 2022–2023 season. Simultaneously, the shot speed data finds its way to a designated topic within our MSK cluster. His skills and areas of expertise include application development, data science, and machine learning (ML). fast shots.

AWS 123

AWS Apache Kafka Data Scientist Data Science 123

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. Durga Sury is an ML Solutions Architect on the Amazon SageMaker Service SA team. She is passionate about making machine learning accessible to everyone.

AWS 99

AWS Data Scientist ML ML 99

Snorkel AI

FEBRUARY 6, 2023

He presented at Snorkel AI’s 2022 Future of Data Centric AI (FDCAI) Conference. It just happened that when the system started clustering the images, it started to make some sort of a sense. The post NASA ML Lead on its WorldView citizen scientist no-code tool appeared first on Snorkel AI.

ML 52

ML ML Supervised Learning Deep Learning 52

Snorkel AI

FEBRUARY 6, 2023

He presented at Snorkel AI’s 2022 Future of Data Centric AI (FDCAI) Conference. It just happened that when the system started clustering the images, it started to make some sort of a sense. The post NASA ML Lead on its WorldView citizen scientist no-code tool appeared first on Snorkel AI.

ML 52

ML ML Supervised Learning Deep Learning 52

AWS Machine Learning Blog

MAY 15, 2023

Getir used Amazon Forecast , a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts, to increase revenue by four percent and reduce waste cost by 50 percent. She then joined Getir in 2022 as a Senior Data Scientist working on forecasting and search engine projects.

Algorithm 94

Algorithm Data Scientist Machine Learning Machine Learning 94

AWS Machine Learning Blog

MARCH 30, 2023

This style of play is also evident when you look at the ball recovery times for the first 24 match days in the 2022/23 season. Let’s look at certain games played by Cologne in the 2022/23 season. Fotinos Kyriakides is an ML Engineer with AWS Professional Services. Cologne achieved an incredible ball recovery time of 13.4

AWS 98

AWS Machine Learning Machine Learning Apache Kafka 98

Mlearning.ai

JULY 6, 2023

2022’s paper. 2022 Deep learning notoriously needs a lot of data in training. 2022 Figure 3. 2022 Figure 4. 2022 for further reference. The sub-categories of this approach are negative sampling, clustering, knowledge distillation, and redundancy reduction. Image: Wang et al., Taxonomy of SSL.

Supervised Learning 52

Supervised Learning Deep Learning Deep Learning K-nearest Neighbors 52