AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. Interact with several demos that feature new applications, including a competition that involves using generative AI tech to pilot a drone around an obstacle course. Reserve your seat now!

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Flipboard

NOVEMBER 21, 2024

We use Amazon SageMaker Pipelines , which helps automate the different steps, including data preparation, fine-tuning, and creating the model. We demonstrated an end-to-end solution that uses SageMaker Pipelines to orchestrate the steps of data preparation, model training, evaluation, and deployment.

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DagsHub

MAY 27, 2024

In simple terms, data annotation helps the algorithms distinguish between what's important and what's not with the help of labels and annotations, allowing them to make informed decisions and predictions. Now you might be wondering, why exactly we need these annotation tools when we can label the ML data on our own.

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AWS Machine Learning Blog

OCTOBER 8, 2024

SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment. Data preparation The foundation of any machine learning project is data preparation.

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Towards AI

JUNE 25, 2024

As a Python user, I find the {pySpark} library super handy for leveraging Spark’s capacity to speed up data processing in machine learning projects. This practice vastly enhances the speed of my data preparation for machine learning projects. within each project folder. distinct().count()

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The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. Pay-as-you-go pricing makes it easy to scale when needed.

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AWS Machine Learning Blog

JUNE 3, 2024

SageMaker Data Wrangler has also been integrated into SageMaker Canvas, reducing the time it takes to import, prepare, transform, featurize, and analyze data. In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing.

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ODSC - Open Data Science

MARCH 18, 2025

As the author of Deep Learning Illustrated, a #1 bestseller translated into seven languages, and an Oxford PhD with over a decade of machine learning research, Jon brings unparalleled expertise to thestage. A prolific educator, Julien shares his knowledge through code demos, blogs, and YouTube, making complex AI accessible.

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Julien Simon

MARCH 31, 2025

Data Preparation The first step in building the RAG chatbot is to prepare the data. In this case, the data consists of PDF documents, which can be research articles or any other PDF files of your choice. Hugging Face Spaces provide a platform for hosting and sharing machine learning applications.

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Heartbeat

JUNE 5, 2023

In recent years, machine learning has exploded in popularity because of its wide range of potential uses in fields including healthcare, finance, eCommerce, and the arts. However, managing machine learning projects can be challenging, especially as the size and complexity of the data and models increase.

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Flipboard

DECEMBER 11, 2024

However, building advanced data-driven applications poses several challenges. First, it can be time consuming for users to learn multiple services development experiences. Third, configuring and governing access to appropriate users for data, code, development artifacts, and compute resources across services is a manual process.

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DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Learn more at DataRobot.com/Snowflake.

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AWS Machine Learning Blog

FEBRUARY 18, 2025

The following sections further explain the main components of the solution: ETL pipelines to transform the log data, agentic RAG implementation, and the chat application. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

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Flipboard

AUGUST 17, 2023

Amazon Redshift is the most popular cloud data warehouse that is used by tens of thousands of customers to analyze exabytes of data every day. Deploy the CloudFormation template Complete the following steps to deploy the CloudFormation template: Save the CloudFormation template sm-redshift-demo-vpc-cfn-v1.yaml yaml locally.

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IBM Journey to AI blog

DECEMBER 7, 2023

Increased operational efficiency benefits Reduced data preparation time : OLAP data preparation capabilities streamline data analysis processes, saving time and resources. IBM watsonx.data is the next generation OLAP system that can help you make the most of your data.

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AWS Machine Learning Blog

MAY 31, 2024

Data preparation Before creating a knowledge base using Knowledge Bases for Amazon Bedrock, it’s essential to prepare the data to augment the FM in a RAG implementation. For this example, we created a bucket with versioning enabled with the name bedrock-kb-demo-gdpr.

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Snorkel AI

NOVEMBER 1, 2023

After accessing unstructured data in Google Cloud with a few clicks via the native BigQuery connector , machine learning teams can select PaLM 2 and evaluate zero-shot results. R3 Snorkel Flow release is an upgraded Python SDK, now enhanced with advanced data preparation capabilities that enable on-the-fly transformations.

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Tableau

FEBRUARY 22, 2021

release, we’re delivering the first integration of Salesforce’s artificial intelligence (AI) and machine learning (ML) capabilities in Tableau. We’re bringing powerful data science techniques closer to the business, beginning with Einstein Discovery in Tableau. February 23, 2021 - 3:55am. March 23, 2021.

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AWS Machine Learning Blog

AUGUST 26, 2024

Users can input audio, video, or text into GenASL, which generates an ASL avatar video that interprets the provided data. The solution uses AWS AI and machine learning (AI/ML) services, including Amazon Transcribe , Amazon SageMaker , Amazon Bedrock , and FMs. You can use this URL to access the GenASL demo application.

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AWS Machine Learning Blog

JULY 5, 2023

What if we could apply deep learning techniques to common areas that drive vehicle failures, unplanned downtime, and repair costs? SageMaker Jumpstart is the machine learning (ML) hub of Amazon SageMaker , providing pre-trained, publicly available models for a wide range of problem types to help you get started with ML.

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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.

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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.

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Precisely

JULY 18, 2024

Ensures consistent, high-quality data is readily available to foster innovation and enable you to drive competitive advantage in your markets through advanced analytics and machine learning. You must be able to continuously catalog, profile, and identify the most frequently used data. Increase metadata maturity.

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AWS Machine Learning Blog

AUGUST 14, 2023

Some of the models offer capabilities for you to fine-tune them with your own data. SageMaker JumpStart also provides solution templates that set up infrastructure for common use cases, and executable example notebooks for machine learning (ML) with SageMaker. script to preprocess and index the provided demo data.

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AWS Machine Learning Blog

SEPTEMBER 25, 2024

Solution overview In this solution, we start with data preparation, where the raw datasets can be stored in an Amazon Simple Storage Service (Amazon S3) bucket. We provide a Jupyter notebook to preprocess the raw data and use the Amazon Titan Multimodal Embeddings model to convert the image and text into embedding vectors.

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Towards AI

JANUARY 31, 2023

Then I thought to myself, why don’t I build a machine-learning model and embedded it in an app so that people can easily use it to identify them and also get suggestions on the different attires they can sew with them. Here is a quick demo of how it works Let's now dive deep into how I went about the project. Sure, it does.

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IBM Journey to AI blog

MARCH 14, 2024

  Request a live demo or start a proof of concept with Amazon RDS for Db2 Db2 Warehouse SaaS on AWS The cloud-native Db2 Warehouse fulfills your price and performance objectives for mission-critical operational analytics, business intelligence (BI) and mixed workloads.

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Snorkel AI

NOVEMBER 1, 2023

After accessing unstructured data in Google Cloud with a few clicks via the native BigQuery connector , machine learning teams can select PaLM 2 and evaluate zero-shot results. R3 Snorkel Flow release is an upgraded Python SDK, now enhanced with advanced data preparation capabilities that enable on-the-fly transformations.

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DataRobot Blog

OCTOBER 3, 2017

Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure. DataRobot Data Prep. free trial. Try now for free.

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Snorkel AI

JANUARY 26, 2024

Data scientists can best improve LLM performance on specific tasks by feeding them the right data prepared in the right way. Programmatically scale human preferences and alignment in GenAI Hoang Tran, Machine Learning Engineer at Snorkel AI, explained how he used scalable tools to align language models with human preferences.

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DataRobot Blog

FEBRUARY 15, 2023

The demo from the session highlights unique and differentiated capabilities that empower all users—from the analysts to the data scientists and even the person at the end of the journey who just needs to access an instant price estimate. After setting up your project, you can get started.

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Explosion

NOVEMBER 16, 2021

Machine Learning Engineers who turn prototypes into production-ready software face difficulties with the lack of tooling and best-practices. It all boils down to your config.cfg file and data preparation script, and the spaCy CLI handles everything. Here’s my take on how it works, and how it can ramp-up your team!

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Snorkel AI

MARCH 19, 2024

The main lever for optimizing LLMs and delivering both production-level accuracy and competitive advantage lies in a company’s own data. Developing AI applications has traditionally been a linear, “model-centric” process in which machine learning models could be optimized by tuning specific parameters. Book a demo today.

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Tableau

FEBRUARY 22, 2021

release, we’re delivering the first integration of Salesforce’s artificial intelligence (AI) and machine learning (ML) capabilities in Tableau. We’re bringing powerful data science techniques closer to the business, beginning with Einstein Discovery in Tableau. February 23, 2021 - 3:55am. March 23, 2021.

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Snorkel AI

MARCH 19, 2024

The main lever for optimizing LLMs and delivering both production-level accuracy and competitive advantage lies in a company’s own data. Developing AI applications has traditionally been a linear, “model-centric” process in which machine learning models could be optimized by tuning specific parameters. Book a demo today.

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Iguazio

FEBRUARY 8, 2024

LLMOps (Large Language Model Operations), is a specialized domain within the broader field of machine learning operations (MLOps). This includes version control, tracking experiments and documentation to foster collaboration among data scientists, engineers and researchers. What is LLMOps? What is MLOps?

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