Mlearning.ai

APRIL 24, 2023

Learning about the framework of a service cloud platform is time consuming and frustrating because there is a lot of new information from many different computing fields (computer science/database, software engineering/developers, data science/scientific engineering & computing/research).

Azure 52

Azure SQL Database Python 52

Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. Below follows a transcript of their conversation, lightly edited for readability. Mayee Chen: Okay. Hi everyone.

K-nearest Neighbors 52

K-nearest Neighbors Clustering AI AI 52

Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. Below follows a transcript of their conversation, lightly edited for readability. Mayee Chen: Okay. Hi everyone.

K-nearest Neighbors 52

K-nearest Neighbors Clustering AI AI 52

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Prerequisites To continue with the examples in this post, you need to create the required AWS resources.

ML 93

ML ML AWS Data Warehouse 93

AWS Machine Learning Blog

SEPTEMBER 18, 2023

With Ray and AIR, the same Python code can scale seamlessly from a laptop to a large cluster. The managed infrastructure of SageMaker and features like processing jobs, training jobs, and hyperparameter tuning jobs can use Ray libraries underneath for distributed computing. You can specify resource requirements in actors too.

Machine Learning 102

Machine Learning Machine Learning ML ML 102

AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. For Account ID , enter the AWS account ID of the owner of the accepter VPC.

AWS 70

AWS Analytics Analytics Machine Learning 70

AWS Machine Learning Blog

AUGUST 22, 2023

Usually, if the dataset or model is too large to be trained on a single instance, distributed training allows for multiple instances within a cluster to be used and distribute either data or model partitions across those instances during the training process. Each account or Region has its own training instances.

Machine Learning 71

Machine Learning Machine Learning AWS ML 71

Dataconomy

MARCH 13, 2023

Here are some of the essential tools and platforms that you need to consider: Cloud platforms Cloud platforms such as AWS , Google Cloud , and Microsoft Azure provide a range of services and tools that make it easier to develop, deploy, and manage AI applications.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

AWS Machine Learning Blog

JUNE 7, 2023

Training setup We provisioned a managed compute cluster comprised of 16 dl1.24xlarge instances using AWS Batch. We developed an AWS Batch workshop that illustrates the steps to set up the distributed training cluster with AWS Batch. in Computer Science from the University of Lille.

AWS 67

AWS Clustering Deep Learning Deep Learning 67

AWS Machine Learning Blog

JANUARY 20, 2023

In this post, we discuss how CCC Intelligent Solutions (CCC) combined Amazon SageMaker with other AWS services to create a custom solution capable of hosting the types of complex artificial intelligence (AI) models envisioned. Step-by-step solution Step 1 A client makes a request to the AWS API Gateway endpoint.

AWS 65

AWS AI AI Computer Science 65

AWS Machine Learning Blog

FEBRUARY 10, 2023

As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. She received her Ph.D.

ML 66

ML ML Machine Learning Machine Learning 66

AWS Machine Learning Blog

MAY 24, 2023

You can efficiently deploy the pre-trained J2-jumbo-instruct, or other Jurassic-2 models available on AWS Marketplace, into your own own virtual private cloud (VPC) using Amazon SageMaker. 24xlarge") # Create a Sgaemkaer endpoint then deploy a pre-trained J2-jumbo-instruct-v1 model from AWS Market Place.

AI 73

AI AI AWS ML 73

O'Reilly Media

OCTOBER 19, 2021

Cloud-based data warehouses, such as Snowflake , AWS’ portfolio of databases like RDS, Redshift or Aurora , or an S3-based data lake , are a great match to ML use cases since they tend to be much more scalable than traditional databases, both in terms of the data set sizes as well as query patterns. Software Development Layers.

ML 138

ML ML Data Scientist AWS 138

AWS Machine Learning Blog

APRIL 18, 2023

We serve developers and enterprises of all sizes through AWS, which offers a broad set of global compute, storage, database, and other service offerings. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

ML 66

ML ML Deep Learning Deep Learning 66

AWS Machine Learning Blog

APRIL 18, 2023

We serve developers and enterprises of all sizes through AWS, which offers a broad set of global compute, storage, database, and other service offerings. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

ML 52

ML ML Deep Learning Deep Learning 52

The MLOps Blog

OCTOBER 3, 2023

Mikiko Bazeley: Most people are really surprised to hear that my background in college was not computer science. For example, you can use BigQuery , AWS , or Azure. I would need to have the infrastructure to perform computations. It can be a cluster run by Kubernetes or maybe something else. How awful are they?”

ML 52

ML ML Data Scientist Machine Learning 52

Flipboard

NOVEMBER 24, 2023

In this post, we show you how SnapLogic , an AWS customer, used Amazon Bedrock to power their SnapGPT product through automated creation of these complex DSL artifacts from human language. SnapLogic background SnapLogic is an AWS customer on a mission to bring enterprise automation to the world.

Database 112

Database AWS ETL SQL 112

AWS Machine Learning Blog

NOVEMBER 1, 2023

Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). About the authors Alfred Shen is a Senior AI/ML Specialist at AWS. Dr. Changsha Ma is an AI/ML Specialist at AWS.

AWS 94

AWS Clustering Deep Learning Deep Learning 94