ML @ CMU

MARCH 31, 2023

Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. Model explanations have been touted as crucial information to facilitate human-ML interactions in many real-world applications where end users make decisions informed by ML predictions.

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insideBIGDATA

APRIL 25, 2023

This checklist from our friends over at Arize covers the essential elements to consider when evaluating an ML observability platform. Whether you’re readying an RFP or assessing individual platforms, this buyer’s guide can help with product and technical requirements to consider across a number of areas discussed in this useful resource.

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KDnuggets

JUNE 26, 2023

Or have you ever questioned whether AI and ML have the capabilities to predict future events as Baba Vanga did? For suppose if AI and ML have the capabilities, then up to how extent can it predict? Have you ever wondered how fortune tellers, astrologers, or our well-known Baba Vanga used to predict future events?

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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KDnuggets

OCTOBER 24, 2022

TheSequence recently released the first ever ML Chain Landscape shaped by data scientists, a new landscape that would be able to address the entire ML value chain.

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KDnuggets

DECEMBER 29, 2021

AI/ML systems have a wide range of applications in a variety of industries and sectors, and this article highlights the top ways AI/ML will impact your small business in 2022.

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KDnuggets

MARCH 9, 2022

Four-day conference offers hundreds of learning and development opportunities in AI, ML, DL, robotics, data science and high performance computing for developers at all levels.

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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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Flipboard

NOVEMBER 26, 2023

Amazon Redshift ML empowers data analysts and database developers to integrate the capabilities of machine learning and artificial intelligence into …

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Machine Learning Research at Apple

APRIL 26, 2023

Existing novice-friendly machine learning (ML) modeling tools center around a solo user experience, where a single user collects only their own data to build a model. To address this issue, we created Co-ML – a tablet-based app for learners…

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KDnuggets

MAY 31, 2022

Add Layer to your existing ML code and quickly get a rich model and data registry with experiment tracking!

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KDnuggets

AUGUST 30, 2022

Doug Turnbull’s ‘ML Powered Search’ Live Cohort starts Oct 11 on Sphere. Join now to learn to create ranking solutions that maximize conversions and clicks, identify & improve challenging search queries using ML, and more.

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KDnuggets

JUNE 29, 2022

So how can an organization stay agile within an ever-shifting ML landscape? Part of the answer lies with establishing a modular ML architecture. Comet will be joined on July 6th in a live webinar by the AI Infrastructure Alliance and Superb AI to discuss how to accelerate AI value with modular MLOps. Register now.

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KDnuggets

DECEMBER 16, 2021

Let’s take a closer look on Cloud ML market in 2021 in retrospective (with occasional drills into realities of 2020, too). Read this in-depth analysis.

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Machine Learning Research at Apple

JUNE 5, 2023

Existing novice-friendly machine learning (ML) modeling tools center around a solo user experience, where a single user collects only their own data to build a model. To address this issue, we created Co-ML – a tablet-based app for learners…

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insideBIGDATA

AUGUST 26, 2023

Fennel is a modern feature engineering platform and helps you author, compute, store, serve, monitor & govern both real-time and batch ML features. In the video presentation below CEO Nikhil Garg introduces his company's real-time feature platform Fennel.

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insideBIGDATA

AUGUST 29, 2023

In this contributed article, Maxim Melamedov, CEO and co-founder of Zesty, explores the cost-savings potential behind leveraging AI/ML in the cloud. By implementing tools capable of real-time decision making and analysis, companies can truly unlock the promise of the cloud.

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KDnuggets

MARCH 17, 2022

In this short blog, we’ll review the process of taking a POC data science pipeline (ML/Deep learning/NLP) that was conducted on Google Colab, and transforming it into a pipeline that can run parallel at scale and works with Git so the team can collaborate on.

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Google Research AI blog

MAY 23, 2023

However, with machine learning (ML), we have an opportunity to automate and streamline the code review process, e.g., by proposing code changes based on a comment’s text. As of today, code-change authors at Google address a substantial amount of reviewer comments by applying an ML-suggested edit. 3-way-merge UX in IDE.

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KDnuggets

NOVEMBER 30, 2022

Synthetic data generation is a solution that allows citizen data scientists and auto ML users to quickly and safely create and use business-critical data assets. Benefits go beyond democratizing data access, and even those with privileged data access build synthetic data generators into their workflows.

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Hacker News

SEPTEMBER 20, 2023

In this post, we’ll write a ML model compiler from scratch. We make micrograd fly with a little compiler magic.

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AWS Machine Learning Blog

NOVEMBER 2, 2023

Amazon SageMaker Canvas now supports deploying machine learning (ML) models to real-time inferencing endpoints, allowing you take your ML models to production and drive action based on ML-powered insights. It also makes operationalizing ML models more accessible to individuals, without the need to write code.

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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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insideBIGDATA

JULY 21, 2023

In this video presentation, Aleksa Gordić explains what it takes to scale ML models up to trillions of parameters! He covers the fundamental ideas behind all of the recent big ML models like Meta's OPT-175B, BigScience BLOOM 176B, EleutherAI's GPT-NeoX-20B, GPT-J, OpenAI's GPT-3, Google's PaLM, DeepMind's Chinchilla/Gopher models, etc.

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KDnuggets

FEBRUARY 8, 2023

Chip Huyen’s new interactive course shares frameworks, case studies and live coding/infrastructure examples to help your team avoid these pitfalls and successfully leverage ML.

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Flipboard

SEPTEMBER 16, 2023

Machine Learning (ML), a subfield of Artificial Intelligence (AI), … These third-party libraries are an essential part of any AI developer’s toolkit.

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KDnuggets

NOVEMBER 30, 2021

The new platform provides a single API to abstract dozens of ML frameworks and databases.

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KDnuggets

MARCH 23, 2022

How sound risk management acts as a catalyst to building successful AI/ML models.

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Julien Simon

OCTOBER 8, 2023

In this video, I show you how to deploy Hugging Face models in one click on Azure, thanks to the model catalog in Azure ML Studio. link] To get started, you simply need to navigate to the Azure ML Studio website and open the model catalog. Then, I run a small Python example to predict with the model.

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ML @ CMU

MARCH 30, 2023

Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. Model explanations have been touted as crucial information to facilitate human-ML interactions in many real-world applications where end users make decisions informed by ML predictions.

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AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

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Towards AI

AUGUST 6, 2023

Getting Started with Visual Blocks for ML This member-only story is on us. Photo by EJ Strat on Unsplash Visual Blocks for ML is an open-source, visual programming framework developed by Google. ⚡️Continue reading to find out how this framework can help accelerate your ML workflows! Upgrade to access all of Medium.

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Flipboard

OCTOBER 25, 2023

However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data. Amazon Rekognition – This image and video analysis service uses ML to extract metadata from visual data.

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Towards AI

NOVEMBER 20, 2023

Last Updated on November 21, 2023 by Editorial Team Author(s): Amit Chauhan Originally published on Towards AI.

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Dataversity

SEPTEMBER 4, 2023

The list of use cases powered by artificial intelligence (AI) and machine learning (ML) technologies is growing exponentially across nearly every business sector.

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Mlearning.ai

NOVEMBER 29, 2023

How to Use Machine Learning (ML) for Time Series Forecasting — NIX United The modern market pace calls for a respective competitive edge. ML-based predictive models nowadays may consider time-dependent components — seasonality, trends, cycles, irregular components, etc. — to

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AWS Machine Learning Blog

NOVEMBER 27, 2023

In this post, we demonstrate how business analysts and citizen data scientists can create machine learning (ML) models, without any code, in Amazon SageMaker Canvas and deploy trained models for integration with Salesforce Einstein Studio to create powerful business applications. After your model begins building, you can leave the page.

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