Towards AI

JUNE 25, 2024

🧰 The dummy data While Spark is famous for its ability to work with big data, for demo purposes, I have created a small dataset with an obvious duplicate issue. We will use this table to demo and test our custom functions. Do you notice that the two ID fields, ID1 and ID2, do not form a primary key? distinct().count()

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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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AWS Machine Learning Blog

APRIL 11, 2023

Developing web interfaces to interact with a machine learning (ML) model is a tedious task. With Streamlit , developing demo applications for your ML solution is easy. Streamlit is an open-source Python library that makes it easy to create and share web apps for ML and data science. sh setup.sh is modified on disk.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

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AWS Machine Learning Blog

JUNE 7, 2023

You can now retrain machine learning (ML) models and automate batch prediction workflows with updated datasets in Amazon SageMaker Canvas , thereby making it easier to constantly learn and improve the model performance and drive efficiency. An ML model’s effectiveness depends on the quality and relevance of the data it’s trained on.

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IBM Data Science in Practice

MARCH 4, 2024

This works for both Predictive ML and LLMs. For Predictive ML, both development and runtime metrics can be monitored for any model including quality metrics, drift, and fairness monitoring. Each of these calculations can be done for any vendor at development time. Details in our documentation here.)

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Dataconomy

JUNE 16, 2023

The cloud DLP solution from Gamma AI has the highest data detection accuracy in the market and comes packed with ML-powered data classification profiles. For a free initial consultation call, you can email sales@gammanet.com or click “Request a Demo” on the Gamma website ([link] Go to the Gamma.AI How to use Gamme AI?

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ODSC - Open Data Science

OCTOBER 7, 2024

Come and be part of ODSC West’s AI Expo & Demo Hall ! Vessl AI: Built for MLOps teams, Vessl AI simplifies ML workflows from model training to deployment, improving efficiency. Meet a few of our top-tier AI partners and learn about the tools and insights to drive your AI initiatives forward.

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Snorkel AI

JUNE 27, 2024

AWS provides a robust framework for responsible AI development with Amazon SageMaker, a fully managed service that brings together a broad set of tools to build, train, and deploy generative AI and machine learning (ML) models. Our relationship with AWS helps organizations around the globe accelerate the demo-to-production pipeline.

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phData

MAY 17, 2024

The brand-new Forecasting tool created on Snowflake Data Cloud Cortex ML allows you to do just that. What is Cortex ML, and Why Does it Matter? Cortex ML is Snowflake’s newest feature, added to enhance the ease of use and low-code functionality of your business’s machine learning needs.

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AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. These models are then pushed to an Amazon Simple Storage Service (Amazon S3) bucket using DVC, a version control tool for ML models. Thirdly, there are improvements to demos and the extension for Spark.

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AWS Machine Learning Blog

MAY 4, 2023

This post provides an overview of generative AI with a real customer use case, provides a concise description and outlines its benefits, references an easy-to-follow demo of AWS DeepComposer for creating new musical compositions, and outlines how to get started using Amazon SageMaker JumpStart for deploying GPT2, Stable Diffusion 2.0,

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PyImageSearch

DECEMBER 11, 2023

But again, stick around for a surprise demo at the end. ? 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. MakerSuite Sprint: This session involved participants building ML applications using the PaLM API.

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Flipboard

DECEMBER 11, 2024

Second, because data, code, and other development artifacts like machine learning (ML) models are stored within different services, it can be cumbersome for users to understand how they interact with each other and make changes. Under Quick setup settings , for Name , enter a name (for example, demo). Choose Continue.

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PyImageSearch

DECEMBER 4, 2023

Home Table of Contents ML Days in Tashkent — Day 1: City Tour Arriving at Tashkent! But stick around for a surprise demo at the end. A Peek into the Google ML Community Summit The summit was a melting pot of ideas and innovations in the Machine Learning field.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Let’s learn about the services we will use to make this happen.

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Iguazio

DECEMBER 18, 2023

For data science practitioners, productization is key, just like any other AI or ML technology. Successful demos alone just won’t cut it, and they will need to take implementation efforts into consideration from the get-go, and not just as an afterthought. AI/ML Predictions for the New Year appeared first on Iguazio.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Amazon SageMaker Studio offers a comprehensive set of capabilities for machine learning (ML) practitioners and data scientists. These include a fully managed AI development environment with an integrated development environment (IDE), simplifying the end-to-end ML workflow.

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IBM Data Science in Practice

MARCH 13, 2023

Learn more about how Disparate-Impact Remover works and check out an AIF360 code demo. Learn more about how Learning Fair Representations works and check out an AIF360 code demo. Learn more about how Optimized Pre-Processing works and check out an AIF360 code demo. What about other bias-mitigation methods?

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IBM Data Science in Practice

MAY 21, 2024

AI efforts, whether generative AI or predictive ML, are organized into use cases. This creates a central inventory to document AI and ML efforts, including the ability to assign an overall risk score for each use case. AI Artifact Governance This portion of watsonx.governance is about documentation.

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Data Science Dojo

JULY 17, 2023

Explore the top 10 machine learning demos and discover cutting-edge techniques that will take your skills to the next level. It has a large and active community of users and developers who can provide support and help. It is open-source, so it is free to use and modify. It is a cloud-based platform, so it can be accessed from anywhere.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

Today, we are excited to unveil three generative AI demos, licensed under MIT-0 license : Amazon Kendra with foundational LLM – Utilizes the deep search capabilities of Amazon Kendra combined with the expansive knowledge of LLMs. Having the right setup in place is the first step towards a seamless deployment of the demos.

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DataRobot Blog

SEPTEMBER 1, 2022

IDC 2 predicts that by 2024, 60% of enterprises would have operationalized their ML workflows by using MLOps. The same is true for your ML workflows – you need the ability to navigate change and make strong business decisions. Request a Demo. 1 IDC, MLOps – Where ML Meets DevOps, doc #US48544922, March 2022.

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Snorkel AI

JUNE 27, 2024

AWS provides a robust framework for responsible AI development with Amazon SageMaker, a fully managed service that brings together a broad set of tools to build, train, and deploy generative AI and machine learning (ML) models. Our relationship with AWS helps organizations around the globe accelerate the demo-to-production pipeline.

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ODSC - Open Data Science

OCTOBER 19, 2023

Grab one for access to Keynote Talks, Demo Talks, the AI Expo and Demo Hall, and Extra Events. Find Your AI Solutions at the ODSC West AI Expo Learn about the best AI solutions for your organization at the ODSC West AI Expo & Demo Hall during these Demo Theater sessions! Attend in-person or virtually!

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DataRobot Blog

MARCH 30, 2022

Composable ML. This past summer, DataRobot announced the addition of Composable ML to our AI Cloud platform. However, with the advent of Composable ML, I now have access to built-in sentiment analysis tasks in DataRobot to preprocess the lyrics for me. See DataRobot Composable ML in Action. Request a demo.

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AWS Machine Learning Blog

NOVEMBER 10, 2023

Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. It provides key functionality that allows you to focus on the ML problem at hand while automatically keeping track of the trials and results. We use a Random Forest from SkLearn.

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The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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AWS Machine Learning Blog

DECEMBER 15, 2023

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas , allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Enter a connection name such as demo and choose your desired Amazon DocumentDB cluster.

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Data Science Dojo

OCTOBER 25, 2023

Azure ML Model Catalog Within the Azure model catalog , you can effortlessly locate the Llama 2 model developed by Meta. This demo provides a non-technical audience with the opportunity to submit queries and toggle between chat modes, simplifying the experience of interacting with Llama 2’s generative abilities.

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AWS Machine Learning Blog

OCTOBER 10, 2023

Machine learning (ML), especially deep learning, requires a large amount of data for improving model performance. It is challenging to centralize such data for ML due to privacy requirements, high cost of data transfer, or operational complexity. The ML framework used at FL clients is TensorFlow.

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The MLOps Blog

OCTOBER 8, 2024

In the machine learning (ML) and artificial intelligence (AI) domain, managing, tracking, and visualizing model training processes is a significant challenge due to the scale and complexity of managed data, models, and resources. Use the plugin by installing it with pip install flytekitplugins-neptune. contact-us.

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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. There are three ways to leverage the core ML technology of Einstein Discovery in Tableau—all with no coding required: . February 23, 2021 - 3:55am. March 23, 2021. Arriving in the 2021.1.3

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AWS Machine Learning Blog

JULY 26, 2023

Hands-on walk through: Foundation Models on SageMaker Lesson 1 slides Lesson 1 hands-on demo resources 2. How to do this with SageMaker Ground Truth Updated reward modeling Hands-on walk through: RLFH on SageMaker Lesson 6 slides Lesson 6 hands-on demo resources 7. Deploying a foundation model Why do we want to deploy models?

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The MLOps Blog

JUNE 4, 2024

TL;DR Using CI/CD workflows to run ML experiments ensures their reproducibility, as all the required information has to be contained under version control. The compute resources offered by GitHub Actions directly are not suitable for larger-scale ML workloads. ML experiments are, by nature, full of uncertainty and surprises.

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Towards AI

AUGUST 6, 2024

TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. The release of Gemma 2 provides an interpretability tool called GemmaScope and an approach to guardrailing by using an ML classifier called ShieldGemma.

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