PyImageSearch

DECEMBER 18, 2023

But again, stick around for a surprise demo at the end. ? This format made for a fast-paced and diverse showcase of ideas and applications in AI and ML. In just 3 minutes, each participant managed to highlight the core of their work, offering insights into the innovative ways in which AI and ML are being applied across various fields.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Model server overview A model server is a software component that provides a runtime environment for deploying and serving machine learning (ML) models. The primary purpose of a model server is to allow effortless integration and efficient deployment of ML models into production systems. For MMEs, each model.py The full model.py

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ML ML AWS Deep Learning 133

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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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.

Data Analysis 195

Data Analysis Data Analysis Tableau Machine Learning 195

Iguazio

APRIL 28, 2025

You can hear more details in the webinar this article is based on, straight from Kaegan Casey, AI/ML Solutions Architect at Seagate. Iguazio allows sharing projects between diverse teams, provides detailed logging of parameters, metrics, and ML artifacts and allows for artifact versioning including labels, tags, associated data etc.

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ML ML Clustering Database 69

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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AI AI Natural Language Processing Data Classification 193

Data Science Dojo

MARCH 28, 2023

Machine learning algorithms require the use of various parameters that govern the learning process. Learn about top 10 machine learning demos in detail Why is hyperparameter tuning important? These parameters are called hyperparameters, and their optimal values are often unknown a priori.

Machine Learning 195

Machine Learning Machine Learning Clean Data Algorithm 195

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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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. We previously explored a single job optimization, visualized the outcomes for SageMaker built-in algorithm, and learned about the impact of particular hyperparameter values.

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ML ML Algorithm Python 123

DataRobot

JUNE 23, 2021

To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. This allows data science teams to incorporate any machine learning algorithm or feature engineering method and seamlessly combine them with hundreds of built-in methods. Run Automated Feature Discovery. Run AutoPilot.

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ML ML Data Scientist Machine Learning 52

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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AI AI ML ML 145

Towards AI

JANUARY 4, 2024

Many times, practitioners feel that they have done everything possible to achieve a good forecast estimate — capturing all available relevant data , proper data cleaning, applying all possible algorithms, and fine-tuning the algorithms & still, results sometimes may not be up to mark! ETS forecast in the test period.

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Algorithm ML ML Machine Learning 105

ODSC - Open Data Science

APRIL 20, 2023

Much can be accomplished at the ODSC East AI Expo and Demo Hall , from connecting with partner representatives to getting caught up on the latest developments in AI applications. This session will use a genetic algorithm to illustrate this technique. Topics covered will range from ML-based recommendations to user-friendly interfaces.

Data Science 52

Data Science Azure AI AI 52

ODSC - Open Data Science

MAY 22, 2023

Training AI-Powered Algorithmic Trading with Python Dr. Yves J. Hilpisch | The AI Quant | CEO The Python Quants & The AI Machine, Adjunct Professor of Computational Finance This session will cover the essential Python topics and skills that will enable you to apply AI and Machine Learning (ML) to Algorithmic Trading.

Data Science 97

Data Science Machine Learning Machine Learning Python 97

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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ML ML Predictive Analytics Machine Learning 52

IBM Journey to AI blog

JUNE 5, 2024

That’s why today’s application analytics platforms rely on artificial intelligence (AI) and machine learning (ML) technology to sift through big data, provide valuable business insights and deliver superior data observability. AI- and ML-generated SaaS analytics enhance: 1. What are application analytics?

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Analytics Analytics AI AI 94

Mlearning.ai

JUNE 26, 2023

Introduction Deepchecks is a groundbreaking open-source Python package that aims to simplify and enhance the process of implementing automated testing for machine learning (ML) models. In this article, we will explore the various aspects of Deepchecks and how it can revolutionize the way we validate and maintain ML models.

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ML ML Machine Learning Machine Learning 52

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. Below, you will find some key factors to consider when assessing MLOps tools and platforms, depending on your needs and preferences. and Pandas or Apache Spark DataFrames.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Iguazio

APRIL 24, 2024

Generative AI is by no means a replacement for the previous wave of AI/ML (now sometimes referred to as ‘traditional AI/ML’), which continues to deliver significant value, and represents a distinct approach with its own advantages. In the end, we explain how MLOps can help accelerate the process and bring these models to production.

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ML ML Data Science Data Scientist 52

DataRobot Blog

AUGUST 3, 2022

How can you save time in understanding the impact of language when working with text in ML models ? The turbocharged language detection feature now uses a deep learning algorithm to identify the language of text even more precisely. For more information, visit DataRobot documentation and schedule a demo. Request a demo.

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AI AI Machine Learning Machine Learning 105

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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Machine Learning Machine Learning ML ML 118

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.

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Tableau ML ML AI 105

AWS Machine Learning Blog

DECEMBER 5, 2024

Automated Reasoning checks help prevent factual errors from hallucinations using sound mathematical, logic-based algorithmic verification and reasoning processes to verify the information generated by a model, so outputs align with provided facts and arent based on hallucinated or inconsistent data.

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AI AI AWS Natural Language Processing 113

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. Everybody can train a model.

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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. Everybody can train a model.

SQL 52

SQL ML ML Python 52

AWS Machine Learning Blog

OCTOBER 23, 2024

The following demo shows Agent Creator in action. At its core, Amazon Bedrock provides the foundational infrastructure for robust performance, security, and scalability for deploying machine learning (ML) models. This integrated architecture not only supports advanced AI functionalities but also makes it easy to use.

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AI AI Database AWS 94

AWS Machine Learning Blog

OCTOBER 2, 2023

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. What is SageMaker JumpStart With SageMaker JumpStart, ML practitioners can choose from a growing list of best-performing foundation models.

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Python ML ML Machine Learning 137

AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic relationships) and the learning of complex relationships and patterns within the data (syntactic relationships).

Natural Language Processing 136

Natural Language Processing AWS Machine Learning Machine Learning 136

Flipboard

FEBRUARY 7, 2023

Amazon SageMaker Studio Lab provides no-cost access to a machine learning (ML) development environment to everyone with an email address. Therefore, you can scale your ML experiments beyond the free compute limitations of Studio Lab and use more powerful compute instances with much bigger datasets on your AWS accounts.

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AWS Machine Learning Blog

JUNE 29, 2023

Some of these solutions use common machine learning (ML) models built on historical interaction patterns, user demographic attributes, product similarities, and group behavior. Amazon Personalize enables developers to build applications powered by the same type of ML technology used by Amazon.com for real-time personalized recommendations.

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AWS ML ML Computer Science 94

Towards AI

FEBRUARY 18, 2025

Building a demo is one thing; scaling it to production is an entirely different beast. It has already inspired me to set new goals for 2025, and I hope it can do the same for other ML engineers. They also inspired a bunch of new potentials for ML engineers. Everything changed when Deepseek burst onto the scene a month ago.

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ML ML Data Quality Algorithm 91

AWS Machine Learning Blog

SEPTEMBER 11, 2024

This solution employs machine learning (ML) for anomaly detection, and doesn’t require users to have prior AI expertise. The application, once deployed, constructs an ML model using the Random Cut Forest (RCF) algorithm. Syed Furqhan is a Senior Software Engineer for AI and ML at AWS. anomalyScore":0.0,"detectionPeriodStartTime":"2024-08-29

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The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

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Python ML ML Database 105

AWS Machine Learning Blog

APRIL 7, 2023

As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations. Choose Manage.

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AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

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AWS AI AI ML 113

DataRobot Blog

MARCH 16, 2023

Why model-driven AI falls short of delivering value Teams that just focus model performance using model-centric and data-centric ML risk missing the big picture business context. DataRobot AI Platform release we’ve broken down the barriers that exist across the ML lifecycle. What Do AI Teams Need to Realize Value from AI?

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AI AI ML ML 98

Flipboard

FEBRUARY 2, 2023

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. We then explain the details of the ML methodology and model training procedures.

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