Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. Azure Synapse Analytics This is the future of data warehousing. If you are at a University or non-profit, you can ask for cash and/or AWS credits. Microsoft Azure.

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AWS Machine Learning Blog

APRIL 4, 2025

They fine-tuned this model using their proprietary dataset and in-house data science expertise. Integration with existing systems on AWS: Lumi seamlessly integrated SageMaker Asynchronous Inference endpoints with their existing loan processing pipeline. The pipeline leverages several AWS services familiar to Lumis team.

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Data Science Dojo

FEBRUARY 20, 2023

It provides a large cluster of clusters on a single machine. Spark is a general-purpose distributed data processing engine that can handle large volumes of data for applications like data analysis, fraud detection, and machine learning. AWS SageMaker also has a CLI for model creation and management.

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AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. First, the AWS Trainium accelerator provides a high-performance, cost-effective, and readily available solution for training and fine-tuning large models.

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Smart Data Collective

MARCH 2, 2022

Data science is a growing profession. Standards and expectations are rapidly changing, especially in regards to the types of technology used to create data science projects. Most data scientists are using some form of DevOps interface these days. Benefits of Kubernetes for Data Science.

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AWS Machine Learning Blog

JANUARY 24, 2024

We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace. Health Insurance Portability and Accountability Act (HIPAA) eligibility and General Data Protection Regulation (GDPR) compliance.

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Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms.

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AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia.

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AWS Machine Learning Blog

MAY 30, 2024

In this post, we introduce the Media Analysis and Policy Evaluation solution, which uses AWS AI and generative AI services to provide a framework to streamline video extraction and evaluation processes. This solution, powered by AWS AI and generative AI services, meets these needs.

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Analytics Vidhya

MAY 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Amazon Elasticsearch Service Amazon Elasticsearch Service is a powerful tool that allows you to perform a number of functions. Let us examine how this powerful tool works behind the scenes.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

In addition to its groundbreaking AI innovations, Zeta Global has harnessed Amazon Elastic Container Service (Amazon ECS) with AWS Fargate to deploy a multitude of smaller models efficiently. These include dbt pipelines, data gathering jobs, training, evaluation, and batch inference jobs for smaller models.

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AWS Machine Learning Blog

MAY 23, 2023

In April 2023, AWS unveiled Amazon Bedrock , which provides a way to build generative AI-powered apps via pre-trained models from startups including AI21 Labs , Anthropic , and Stability AI. Amazon Bedrock also offers access to Titan foundation models, a family of models trained in-house by AWS. Deploy the AWS CDK application.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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AWS Machine Learning Blog

MARCH 15, 2024

The need for federated learning in healthcare Healthcare relies heavily on distributed data sources to make accurate predictions and assessments about patient care. Limiting the available data sources to protect privacy negatively affects result accuracy and, ultimately, the quality of patient care.

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AWS Machine Learning Blog

JUNE 11, 2024

Sprinklr’s specialized AI models streamline data processing, gather valuable insights, and enable workflows and analytics at scale to drive better decision-making and productivity. During this journey, we collaborated with our AWS technical account manager and the Graviton software engineering teams.

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AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. This same interface is also used for provisioning EMR clusters.

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Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

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AWS Machine Learning Blog

FEBRUARY 2, 2024

Because embeddings are an important source of data for NLP models in general and generative AI solutions in particular, we need a way to measure whether our embeddings are changing over time (drifting). Then we use K-Means to identify a set of cluster centers.

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

The SageMaker Python SDK automatically translates your existing workspace environment, and any associated data processing code and datasets, into an SageMaker training job that runs on the training platform. For details, refer to Creating an AWS account. In this post, we use Amazon SageMaker Studio with the Data Science 3.0

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AWS Machine Learning Blog

APRIL 19, 2024

We are excited to announce a new version of the Amazon SageMaker Operators for Kubernetes using the AWS Controllers for Kubernetes (ACK). ACK is a framework for building Kubernetes custom controllers, where each controller communicates with an AWS service API. They are also supported by AWS CloudFormation. Release v1.2.9

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AWS Machine Learning Blog

AUGUST 8, 2024

Webex works with the world’s leading business and productivity apps—including AWS. The following diagram illustrates the WxAI architecture on AWS. The topic clustering model achieves this by clustering all the individually extracted call drivers from a large batch of calls into different topic clusters.

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AWS Machine Learning Blog

MAY 1, 2024

Our unstructured data comes from the Amazon EC2 User Guide for Linux Instances and Amazon EC2 Instance Types documentation, and the structured data is derived from the EC2 Instance On-Demand Pricing for the US East (N. Virginia) AWS Region. file for deploying the solution using the AWS CDK. xlarge instance to $24.78

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AWS Machine Learning Blog

MARCH 30, 2023

The match-related data is collected and ingested using DFL’s DataHub. Metadata of the match is processed within the AWS Lambda function MetaDataIngestion , while positional data is ingested using the AWS Fargate container called MatchLink. Tareq Haschemi is a consultant within AWS Professional Services.

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AWS Machine Learning Blog

DECEMBER 29, 2022

However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling. AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. 1 Public subnet. 1 NAT gateway.

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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. To do this, we provide an AWS CloudFormation template to create a stack that contains the resources.

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AWS Machine Learning Blog

APRIL 17, 2023

In conjunction with tools like RStudio on SageMaker, users are analyzing, transforming, and preparing large amounts of data as part of the data science and ML workflow. Data scientists and data engineers use Apache Spark, Hive, and Presto running on Amazon EMR for large-scale data processing.

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AWS Machine Learning Blog

OCTOBER 2, 2024

In this post, we share AWS guidance that we have learned and developed as part of real-world projects into practical guides oriented towards the AWS Well-Architected Framework , which is used to build production infrastructure and applications on AWS. To learn more, see Log Amazon Bedrock API calls using AWS CloudTrail.

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Mlearning.ai

MAY 23, 2023

While specific requirements may vary depending on the organization and the role, here are the key skills and educational background that are required for entry-level data scientists — Skillset Mathematical and Statistical Foundation Data science heavily relies on mathematical and statistical concepts.

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Flipboard

DECEMBER 6, 2023

Click here to open the AWS console and follow along. The model then uses a clustering algorithm to group the sentences into clusters. The sentences that are closest to the center of each cluster are selected to form the summary. To use one of these models, AWS offers the fully managed service Amazon Bedrock.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care.

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ODSC - Open Data Science

FEBRUARY 17, 2023

The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise. In a change from last year, there’s also a higher demand for those with data analysis skills as well. Having mastery of these two will prove that you know data science and in turn, NLP.

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AWS Machine Learning Blog

JANUARY 13, 2023

Because they’re in a highly regulated domain, HCLS partners and customers seek privacy-preserving mechanisms to manage and analyze large-scale, distributed, and sensitive data. To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data.

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Data Science Dojo

JULY 24, 2023

Each node is capable of processing and storing data independently. Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes.

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Flipboard

MARCH 9, 2023

In this post, we review the technical requirements and application design considerations for fine-tuning and serving hyper-personalized AI models at scale on AWS. For example, the G5 instance type, which is equipped with NVIDIA A10g GPUs (unique to AWS), offers a strong price-performance ratio, both for model training and hosting.

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AWS Machine Learning Blog

OCTOBER 20, 2023

We used AWS machine learning (ML) services like Amazon SageMaker to develop a powerful generalized feed ranker (GFR). In the following sections, we discuss each component and the AWS services used in more detail. One of the major challenges was to run distributed training at scale.

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