Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

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Flipboard

OCTOBER 25, 2023

After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. These services write the output to a data lake.

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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. In addition to several exciting announcements during keynotes, most of the sessions in our track will feature generative AI in one form or another, so we can truly call our track “Generative AI and ML.”

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ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. Using Azure ML, you can train your model in three ways: Automated ML: This is where you upload your data and have the workspace automatically train on your behalf.

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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

SEPTEMBER 27, 2024

Specifically, we cover the computer vision and artificial intelligence (AI) techniques used to combine datasets into a list of prioritized tasks for field teams to investigate and mitigate. Data preparation SageMaker Ground Truth employs a human workforce made up of Northpower volunteers to annotate a set of 10,000 images.

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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.

Machine Learning 112

Machine Learning Machine Learning Data Governance ML 112

ODSC - Open Data Science

APRIL 27, 2023

5 Concerns for ML Safety in the Era of LLMs and Generative AI The growth of large language models and generative AI has spurred new concerns for ML safety and cybersecurity. 5 Data Engineering and Data Science Cloud Options for 2023 AI development is incredibly resource intensive.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

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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SQL Data Lakes Data Analyst AWS 114

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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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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K-nearest Neighbors AWS Clustering Database 170

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.

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IBM Journey to AI blog

OCTOBER 4, 2023

Artificial intelligence (AI) is now at the forefront of how enterprises work with data to help reinvent operations, improve customer experiences, and maintain a competitive advantage. It’s no longer a nice-to-have, but an integral part of a successful data strategy.

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AWS Machine Learning Blog

MARCH 1, 2023

This combination of great models and continuous adaptation is what will lead to a successful machine learning (ML) strategy. MLOps focuses on the intersection of data science and data engineering in combination with existing DevOps practices to streamline model delivery across the ML development lifecycle.

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Data Lakes AWS ML ML 91

IBM Journey to AI blog

JANUARY 19, 2024

Staying ahead of key technology trends By now, it’s abundantly clear that technologies like artificial intelligence (AI) and machine learning (ML) will revolutionize how customer-centric organizations interact and deliver value to all stakeholders, especially their customers.

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Alation

FEBRUARY 1, 2022

Sheer volume of data makes automation with Artificial Intelligence & Machine Learning (AI & ML) an imperative. Menninger outlines how modern data governance practices may deploy a basic repository of data; this can help with some level of automation. Are we maximizing the benefits from data lakes?

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Data Lakes Data Governance ML ML 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

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

Data Science Connect

JULY 28, 2023

Cloud-Based IoT Platforms Cloud-based IoT platforms offer scalable storage and computing resources for handling the massive influx of IoT data. These platforms provide data engineers with the flexibility to develop and deploy IoT applications efficiently.

Internet of Things 130

Internet of Things Data Engineering Data Engineering Data Engineer 130

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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Data Science 101

NOVEMBER 11, 2019

It combines data warehousing and data lakes into a simple query interface for a simple and fast analytics service. Data Science Announcements from Microsoft Ignite Many other services were announced such as: Azure Quantum, Project Silica, R support in Azure ML, and Visual Studio Online. Amazon Web Services.

Cloud Data 95

Cloud Data Data Science Azure Clustering 95

AWS Machine Learning Blog

AUGUST 4, 2023

If you are a returning user to SageMaker Studio, in order to ensure Salesforce Data Cloud is enabled, upgrade to the latest Jupyter and SageMaker Data Wrangler kernels. This completes the setup to enable data access from Salesforce Data Cloud to SageMaker Studio to build AI and machine learning (ML) models.

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AWS Machine Learning Blog

JUNE 18, 2024

More than 170 tech teams used the latest cloud, machine learning and artificial intelligence technologies to build 33 solutions. The attempt is disadvantaged by the current focus on data cleaning, diverting valuable skills away from building ML models for sensor calibration.

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AWS AI AI Python 118

ODSC - Open Data Science

AUGUST 24, 2023

Video of the Week: Vector Search — A gentle introduction Uncover the revolutionary approach of using ML models to create semantic vectors, transforming the way we interact with data. From natural language search to recommendation systems, Zain unveils the power of these vectors in enhancing search accuracy and efficiency.

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Data Lakes Data Science Machine Learning Machine Learning 52

ODSC - Open Data Science

JULY 20, 2023

Popular Machine Learning Libraries, Ethical Interactions Between Humans and AI, and 10 AI Startups in APAC to Follow Demystifying Machine Learning: Popular ML Libraries and Tools In this comprehensive guide, we will demystify machine learning, breaking it down into digestible concepts for beginners, including some popular ML libraries to use.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Dataversity

FEBRUARY 17, 2022

With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.

Machine Learning 52

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 52

Towards AI

MARCH 28, 2024

Elymsyr wants to develop new projects to improve their ML, RL, computer vision, and co-working skills. Streamline ML Workflow with MLflow — II by ronilpatil This article explains how to leverage MLflow to track machine learning experiments, register a model, and serve the model into production. Think a friend would enjoy this too?

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AI AI Data Lakes Azure 73

DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Many find themselves swamped by the volume and complexity of unstructured data.

AI 52

AI AI Data Lakes Database 52

AWS Machine Learning Blog

MARCH 1, 2023

Flywheel creates a data lake (in Amazon S3) in your account where all the training and test data for all versions of the model are managed and stored. Periodically, the new labeled data (to retrain the model) can be made available to flywheel by creating datasets. One for the data lake for Comprehend flywheel.

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Data Lakes AWS ML ML 74

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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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.

Data Science 52

Data Science Data Lakes Machine Learning Machine Learning 52

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data fabric and data mesh as concepts have overlaps.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

ODSC - Open Data Science

OCTOBER 25, 2024

Building an Open, Governed Lakehouse with Apache Iceberg and Apache Polaris (Incubating) Yufei Gu | Senior Software Engineer | Snowflake In this session, you’ll explore how open-source table formats are revolutionizing data architectures by enabling the power and efficiency of data warehouses within data lakes.

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AI AI Data Scientist Data Lakes 52

AWS Machine Learning Blog

JULY 29, 2024

SageMaker endpoints can be registered with Salesforce Data Cloud to activate predictions in Salesforce. He has over 10 years of experience in planning, building, launching, and managing world-class solutions for enterprise customers, including AI/ML and cloud solutions. Follow him on LinkedIn. You can connect with him on LinkedIn.

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IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML).

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AI AI Data Warehouse ML 97

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.

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Machine Learning Machine Learning ML ML 53

ODSC - Open Data Science

JUNE 7, 2023

Wednesday, June 14th Me, my health, and AI: applications in medical diagnostics and prognostics: Sara Khalid | Associate Professor, Senior Research Fellow, Biomedical Data Science and Health Informatics | University of Oxford Iterated and Exponentially Weighted Moving Principal Component Analysis : Dr. Paul A.

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