Towards AI

FEBRUARY 10, 2023

Unlocking the Power of Real-time Predictions: An Introduction to Incremental Machine Learning for Linked Data Event Streams Photo by Isaac Smith on Unsplash This article discusses online machine learning, one of the most exciting subdomains of machine learning theory. But first things first, what is incremental or online machine learning?

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AWS Machine Learning Blog

NOVEMBER 19, 2024

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. We use SageMaker Model Monitor to assess these models’ performance.

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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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databricks

MARCH 6, 2023

ML Virtual Event Enabling Production ML at Scale With Lakehouse March 14, 9 AM PDT / 4 PM GMT Register Now We are.

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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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Analytics Vidhya

DECEMBER 24, 2023

Introduction As we bid farewell to 2023, it’s time to reflect on the groundbreaking events that have shaped the landscape of Artificial Intelligence. From advancements in ML to ethical debates […] The post AI Revolution: The Top 10 AI Milestones of 2023 appeared first on Analytics Vidhya.

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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. And although generative AI has appeared in previous events, this year we’re taking it to the next level. Visit the session catalog to learn about all our generative AI and ML sessions.

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Chatbots Life

APRIL 27, 2024

For enterprise software, AI and ML are like special effects. By examining how AI and ML in enterprise software can drive business success, we aim to highlight these technologies’ transformational potential and underscore their importance in today’s competitive business environment.

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ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. This topic is closely aligned with the Responsible AI track at ODSC West  — an event where experts gather to discuss innovations and challenges in AI.

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PyImageSearch

DECEMBER 4, 2023

Home Table of Contents ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent! This blog is the 1st of a 3-part series: ML Days in Tashkent — Day 1: City Tour (this tutorial) ML Days in Tashkent — Day 2: Sprints and Sessions ML Days in Tashkent — Day 3: Demos and Workshops ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent!

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

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DataRobot Blog

JUNE 1, 2022

Join DataRobot and leading organizations June 7 and 8 at DataRobot AI Experience 2022 (AIX) , a unique virtual event that will help you rapidly unlock the power of AI for your most strategic business initiatives. Join the virtual event sessions in your local time across Asia-Pacific, EMEA, and the Americas. Join DataRobot AIX June 7–8.

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phData

JUNE 5, 2024

Snowflake’s Data Cloud Summit 2024 was full of exciting announcements across all workloads, with a strong emphasis on AI/ML innovations. From Generative AI and Large Language Models (LLMs) to Predictive AI/ML and MLOps capabilities, it’s evident that the Snowflake AI Data Cloud continues to prioritize advanced AI applications.

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PyImageSearch

DECEMBER 11, 2023

The sessions were packed with interesting talks on a variety of topics, and the networking events were a great way to meet new people and make connections. Kicking Off with a Keynote The second day of the Google Machine Learning Community Summit began with an inspiring keynote session by Soonson Kwon, the ML Community Lead at Google.

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Data Science Dojo

SEPTEMBER 8, 2023

Descriptive analytics involves summarizing historical data to extract insights into past events. Diagnostic analytics goes further, aiming to uncover the root causes behind these events. ML encompasses a range of algorithms that enable computers to learn from data without explicit programming. Streamline operations.

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Hacker News

JULY 18, 2024

ABOUT EVENTUAL Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI. Eventual and Daft bridge that gap, making ML/AI workloads easy to run alongside traditional tabular workloads. This is more compute than Frontier, the world's largest supercomputer!

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Heartbeat

MARCH 14, 2024

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionary technologies with the potential to transform the field of engineering. The synergy between engineering and AI/ML creates unprecedented opportunities for efficiency, cost reduction, and innovation. Indium Software Why AI and ML in Engineering?

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The MLOps Blog

APRIL 5, 2023

In this comprehensive guide, we’ll explore the key concepts, challenges, and best practices for ML model packaging, including the different types of packaging formats, techniques, and frameworks. Best practices for ml model packaging Here is how you can package a model efficiently.

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Iguazio

AUGUST 14, 2023

As ML models become increasingly complex and integral to critical decision-making processes, ensuring their optimal performance and reliability has become a paramount concern for technology leaders. What is Observability in ML? What is Model Monitoring?

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AWS Machine Learning Blog

MAY 8, 2024

They focused on improving customer service using data with artificial intelligence (AI) and ML and saw positive results, with their Group AI Maturity increasing from 50% to 80%, according to the TM Forum’s AI Maturity Index. million subscribers, which amounts to 57% of the Sri Lankan mobile market.

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Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results. Is ML engineering a stressful job?

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Mlearning.ai

MARCH 15, 2023

San Francisco has a ton of events but unfortunately residents have to really look hard to find events on a weekly basis. Most events can be found on venue websites or on free event posting sites. I scraped event information from SF Fun Cheap, Eventbrite, and 19hz (an EDM and techno focused SF music event page).

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AWS Machine Learning Blog

DECEMBER 12, 2023

This new workforce requires rapid reskilling and understanding of disruptive services such as artificial intelligence (AI) and machine learning (ML) to drive meaningful outcomes. In this post, we share how Vodafone is advancing its ML skills using AWS DeepRacer and Accenture. Why is machine learning important to Vodafone?

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Mlearning.ai

JUNE 10, 2023

Survival analysis is a statistical methodology designed to analyze time-to-event data, providing valuable insights into the time it takes… Continue reading on MLearning.ai »

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AWS Machine Learning Blog

MAY 10, 2023

You can now register machine learning (ML) models built in Amazon SageMaker Canvas with a single click to the Amazon SageMaker Model Registry , enabling you to operationalize ML models in production. Build ML models and analyze their performance metrics.

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AWS Machine Learning Blog

FEBRUARY 2, 2023

The AWS Professional Services team has partnered with the NFL and Biocore to provide machine learning (ML)-based solutions for identifying helmet impacts from game footage using computer vision (CV) techniques. Therefore, adding more perspectives allows our ML system to identify more impacts that aren’t visible in a single view.

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Heartbeat

SEPTEMBER 18, 2023

Unleashing Innovation and Success: Comet — The Trusted ML Platform for Enterprise Environments Machine learning (ML) is a rapidly developing field, and businesses are increasingly depending on ML platforms to fuel innovation, improve efficiency, and mine data for insights.

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AWS Machine Learning Blog

MAY 10, 2023

Business analysts play a pivotal role in facilitating data-driven business decisions through activities such as the visualization of business metrics and the prediction of future events. Through this capability, ML becomes more accessible to business teams so they can accelerate data-driven decision-making.

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Towards AI

FEBRUARY 21, 2023

In the most speculative scenarios, the fear (or hope depending on who you ask) is that the sophistication, power, and complexity of our models will eventually breach an event horizon of breakaway intelligence, where the system develops the capability to iteratively self-improve both it’s core functionality and it’s own ability to self-improve.

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Flipboard

NOVEMBER 28, 2023

While it might be easier to start looking at an individual machine learning (ML) model and the associated risks in isolation, it’s important to consider the details of the specific application of such a model and the corresponding use case as part of a complete AI system. In this post, we focus on AI system risk, primarily.

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Analytics Vidhya

MARCH 21, 2024

Introduction Conferences, bootcamps, and events with thousands of gatherings might sound overwhelming, but they are beneficial for connecting with like-minded individuals. Participating in these events can lead to valuable collaborations, friendships, and personal growth.

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Mlearning.ai

APRIL 6, 2023

Automate and streamline our ML inference pipeline with SageMaker and Airflow Building an inference data pipeline on large datasets is a challenge many companies face. SageMaker Batch Job Allows you to run batch inference on large datasets and generate predictions in a batch mode using machine learning (ML) models hosted in SageMaker.

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Flipboard

NOVEMBER 21, 2024

Define the text generation configuration AutoMLV2 automates the entire ML process, from data preprocessing to model training and deployment. accept_eula – The access configuration file to control access to the ML model. For this project, we used the Meta Llama2-7B model. SageMaker Autopilot supports fine-tuning a variety of LLMs.

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ODSC - Open Data Science

JUNE 23, 2023

It is given that organizations should have an effective way of managing all information about their security and be capable of addressing security events as they arise. That’s why since its introduction in 2005, security information and event management (SIEM) has been regarded as a vital component of cybersecurity.

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AWS Machine Learning Blog

JANUARY 10, 2024

ML Engineer at Tiger Analytics. The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. Model developers often work together in developing ML models and require a robust MLOps platform to work in.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. The data sync is completed by the Step Functions workflow, and its cadence can be on demand, scheduled, or invoked by an event.

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