Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Choose Continue.

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ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

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Flipboard

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. Run the AWS Glue ML transform job.

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AWS Machine Learning Blog

AUGUST 15, 2024

Starting today, you can interactively prepare large datasets, create end-to-end data flows, and invoke automated machine learning (AutoML) experiments on petabytes of data—a substantial leap from the previous 5 GB limit. Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. Enterprises can use no-code ML solutions to streamline their operations and optimize their decision-making without extensive administrative overhead.

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AWS Machine Learning Blog

AUGUST 8, 2024

As one of the largest AWS customers, Twilio engages with data, artificial intelligence (AI), and machine learning (ML) services to run their daily workloads. Data is the foundational layer for all generative AI and ML applications. The following diagram illustrates the solution architecture.

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Flipboard

NOVEMBER 17, 2023

Amazon SageMaker enables enterprises to build, train, and deploy machine learning (ML) models. Amazon SageMaker JumpStart provides pre-trained models and data to help you get started with ML. MongoDB vector data store MongoDB Atlas Vector Search is a new feature that allows you to store and search vector data in MongoDB.

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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.

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DagsHub

DECEMBER 11, 2023

DVC Released in 2017, Data Version Control ( DVC for short) is an open-source tool created by iterative. DVC can be used for versioning data and models, to track experiments and compare any data, code, parameters models and graphical plots of performance. DVC can efficiently handle large files and machine learning models.

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IBM Journey to AI blog

APRIL 24, 2023

By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement. Data warehouse is the base architecture for artificial intelligence and machine learning (AI/ML) solutions as well. Modern data warehousing technology can handle all data forms.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

In entered the Big Data space in 2013 and continues to explore that area. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon. He is focused on Big Data, Data Lakes, Streaming and batch Analytics services and generative AI technologies.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. As MLOps become more relevant to ML demand for strong software architecture skills will increase as well.

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IBM Journey to AI blog

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. How does an open data lakehouse architecture support AI? All of this supports the use of AI.

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AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts.

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AWS Machine Learning Blog

DECEMBER 4, 2023

We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. SageMaker is a fully managed ML service. This was a crucial aspect in achieving agility in our operations and a seamless integration of our ML efforts.

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Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Well, let’s find out. Artificial intelligence (AI).

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AWS Machine Learning Blog

DECEMBER 18, 2023

By using these capabilities, businesses can efficiently store, manage, and analyze time-series data, enabling data-driven decisions and gaining a competitive edge. If you need an automated workflow or direct ML model integration into apps, Canvas forecasting functions are accessible through APIs.

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phData

SEPTEMBER 20, 2023

On the client side, Snowpark consists of libraries, including the DataFrame API and native Snowpark machine learning (ML) APIs for model development (public preview) and deployment (private preview). The release of Snowpark makes our customers’ lives simpler by unifying their data lake into a complete data platform.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Initially, daily forecasts for each country are formulated through ML models. These daily predictions are subsequently broken down into hourly segments, as depicted in the following graph.

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ODSC - Open Data Science

MARCH 23, 2023

Real-time Analytics & Built-in Machine Learning Models with a Single Database Akmal Chaudhri, Senior Technical Evangelist at SingleStore, explores the importance of delivering real-time experiences in today’s big data industry and how data models and algorithms rely on powerful and versatile data infrastructure.

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AWS Machine Learning Blog

JANUARY 4, 2024

In entered the Big Data space in 2013 and continues to explore that area. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon. Enterprise Solutions Architect at AWS, experienced in Software Engineering, Enterprise Architecture, and AI/ML.

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AWS Machine Learning Blog

APRIL 18, 2023

Amazon Monitron is an end-to-end condition monitoring solution that enables you to start monitoring equipment health with the aid of machine learning (ML) in minutes, so you can implement predictive maintenance and reduce unplanned downtime. For the detailed Amazon Monitron installation guide, refer to Getting started with Amazon Monitron.

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AWS Machine Learning Blog

FEBRUARY 28, 2024

Third, despite the larger adoption of centralized analytics solutions like data lakes and warehouses, complexity rises with different table names and other metadata that is required to create the SQL for the desired sources. About the Authors Sanjeeb Panda is a Data and ML engineer at Amazon.

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AWS Machine Learning Blog

APRIL 30, 2025

ENGIEs One Data team partnered with AWS Professional Services to develop an AI-powered chatbot that enables natural language conversation search within ENGIEs Common Data Hub data lake, over 3 petabytes of data. Daniel Zagyva is a Senior ML Engineer at AWS Professional Services.

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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. In this post, we describe how we used Forecast to achieve these benefits.

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ODSC - Open Data Science

JULY 14, 2023

Time Series Forecasting for Managers — All Forecasts Are Wrong but Some Are Useful Tanvir Ahmed Shaikh | Data Strategist (Director) | Genentech, Inc Time series forecasting remains an under-appreciated technique in data science education, often overshadowed by more popular machine learning methods.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029. At Facebook Messenger, ML powers customer service chatbots.

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Flipboard

MAY 9, 2025

The campaign effectiveness analysis uses advanced natural language processing (NLP) and machine learning (ML) models to evaluate how well the generated marketing content aligns with the campaign objectives while incorporating positive sentiments and avoiding negative ones. Strengthen call to action. Balance cost focus with value proposition.

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AWS Machine Learning Blog

AUGUST 2, 2024

Generative AI empowers organizations to combine their data with the power of machine learning (ML) algorithms to generate human-like content, streamline processes, and unlock innovation. After data is extracted, the job performs document chunking, data cleanup, and postprocessing.

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DagsHub

NOVEMBER 11, 2024

We use data-specific preprocessing and ML algorithms suited to each modality to filter out noise and inconsistencies in unstructured data. NLP cleans and refines content for text data, while audio data benefits from signal processing to remove background noise. Tools like Unstructured.io

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AWS Machine Learning Blog

AUGUST 2, 2023

Amazon Kendra is an intelligent search service powered by machine learning (ML). Amazon Kendra supports a variety of document formats , such as Microsoft Word, PDF, and text from various data sources. Image captioning with GenAI Image description with GenAI involves using ML algorithms to generate textual descriptions of images.

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ODSC - Open Data Science

OCTOBER 20, 2023

You’ll use MLRun, Langchain, and Milvus for this exercise and cover topics like the integration of AI/ML applications, leveraging Python SDKs, as well as building, testing, and tuning your work. In this session, we’ll demonstrate how you can fine-tune a Gen AI model, build a Gen AI application, and deploy it in 20 minutes.

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