Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

Data Integration 98

Data Integration ML ESG Big Data 98

Marktechpost

APRIL 11, 2024

Researchers from Meta developed a machine learning (ML)-based approach to address the challenges of optimizing bandwidth estimation (BWE) and congestion control for real-time communication (RTC) across Meta’s family of apps. Meta’s ML-based approach involves two main components: offline ML model learning and parameter tuning.

Machine Learning 81

Machine Learning ML Categorization Data Quality 81

Google Research AI blog

MARCH 30, 2023

Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. Each step can introduce issues and biases.

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ML Algorithm NLP Neural Network 96

The MLOps Blog

JANUARY 26, 2024

TL;DR Feedback integration is crucial for ML models to meet user needs. A robust ML infrastructure gives teams a competitive advantage. I started my ML journey as an analyst back in 2016. Mailchimp’s ML Platform: genesis, challenges, and objectives Mailchimp is a 20-year-old bootstrapped email marketing company.

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ML Data Scientist Machine Learning ML Engineer 65

Unite.AI

FEBRUARY 7, 2024

Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. However, ML models are challenging to develop and deploy. MLOps are practices that automate and simplify ML workflows and deployments. MLOps make ML models faster, safer, and more reliable in production.

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Machine Learning Large Language Models LLM BERT 294

Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. Machine learning(ML) is evolving at a very fast pace. Machine learning(ML) is evolving at a very fast pace.

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Machine Learning ML Neural Network Algorithm 83

AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.

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ML Machine Learning Data Science Data Drift 84

Marktechpost

MAY 7, 2024

The burgeoning expansion of the data landscape, propelled by the Internet of Things (IoT), presents a pressing challenge: ensuring data quality amidst the deluge of information. However, the quality of that data is paramount, especially given the escalating reliance on Machine Learning (ML) across various industries.

Large Language Models 108

Large Language Models Automation Data Quality ML 108

The MLOps Blog

MAY 9, 2023

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times. If all goes well, of course ?

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ML Machine Learning Metadata Automation 98

The MLOps Blog

MAY 17, 2023

From data processing to quick insights, robust pipelines are a must for any ML system. Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. However, efficient use of ETL pipelines in ML can help make their life much easier.

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ETL ML Machine Learning Data Scientist 59

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. Data forecasting has come a long way since formidable data processing-boosting technologies such as machine learning were introduced.

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Machine Learning ML Neural Network Convolutional Neural Networks 52

AWS Machine Learning Blog

FEBRUARY 27, 2024

In this post, we share how Axfood, a large Swedish food retailer, improved operations and scalability of their existing artificial intelligence (AI) and machine learning (ML) operations by prototyping in close collaboration with AWS experts and using Amazon SageMaker. This is a guest post written by Axfood AB.

Machine Learning 106

Machine Learning DevOps Data Quality Data Scientist 106

Unite.AI

OCTOBER 30, 2023

When unstructured data surfaces during AI development, the DevOps process plays a crucial role in data cleansing, ultimately enhancing the overall model quality. Improving AI quality: AI system effectiveness hinges on data quality. Poor data can distort AI responses.

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DevOps Software Development Automation Artificial Intelligence 310

The MLOps Blog

AUGUST 11, 2023

There comes a time when every ML practitioner realizes that training a model in Jupyter Notebook is just one small part of the entire project. Getting a workflow ready which takes your data from its raw form to predictions while maintaining responsiveness and flexibility is the real deal.

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ML Machine Learning Data Ingestion Deep Learning 52

Unite.AI

DECEMBER 23, 2023

Some of the APM strategies employed for this include: Predictive Maintenance: By using modern AI/ML capabilities to analyze big data , this strategy can monitor an asset’s health and forecast maintenance. Root Cause Analysis (RCA): This strategy emphasizes understanding the root causes of asset failures in a structured manner.

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Data Quality Big Data Artificial Intelligence Artificial Intelligence 182

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.

ML 75

ML Categorization AI AI 75

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Marktechpost

MARCH 11, 2024

Their solution focuses on filtering image-text data, a novel approach that introduces a nuanced scoring system for data quality evaluation, offering a more refined assessment than its predecessors. The research introduces a comprehensive scoring system that evaluates the quality of image-text pairs across four distinct metrics.

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Machine Learning Data Quality Artificial Intelligence Artificial Intelligence 112

Flipboard

JUNE 15, 2023

Read the full series here: Building the foundation for customer data quality. The rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies is pushing the boundaries of what can be achieved in marketing, customer experience … This article is part of a VB special issue.

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Generative AI Data Quality Artificial Intelligence Artificial Intelligence 114

Aiiot Talk

APRIL 30, 2024

Traditionally, NDT relied heavily on manual inspection techniques and human expertise, but the process has undergone a transformative evolution with the advent of AI and machine learning (ML). AI and ML are augmenting human capabilities and advanced data analysis, paving the way for safer and more reliable NDT processes in the following ways.

Automation 130

Automation Algorithm AI AI 130

IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Metadata Data Quality Data Discovery Data Scientist 130

Marktechpost

APRIL 15, 2024

As climate change continuously threatens our planet and the existence of life on it, integrating machine learning (ML) and artificial intelligence (AI) into this arena offers promising solutions to predict and mitigate its impacts effectively.

Machine Learning 87

Machine Learning Data Analysis ML Artificial Intelligence 87

Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. A transcript of the talk follows.

ML 52

ML Machine Learning Data Quality Algorithm 52

Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. A transcript of the talk follows.

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ML Machine Learning Data Quality Algorithm 52

The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Yeah.

ML 52

ML Data Scientist Software Engineer Machine Learning 52

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). Pre-trained models were applied in many different domains and started to be considered critical for ML research [1]. 8) ML for Science The architecture of AlphaFold 2.0. Credit for the title image: Liu et al. What happened?  

NLP 52

NLP ML BERT Computational Linguistics 52

Pickl AI

OCTOBER 9, 2023

This case study sheds light on how a leading global retailer, XYZ Retail, harnessed the power of Machine Learning (ML) to revolutionize its demand forecasting process. Real-time Updates: ML models continuously updated forecasts, allowing XYZ Retail to make agile decisions regarding inventory management, promotions, and supply chain logistics.

Machine Learning 98

Machine Learning Algorithm ML Data Quality 98

Marktechpost

JANUARY 1, 2024

Researchers from Microsoft have introduced a novel approach to generate diverse, high-quality instruction data from open-source code, thereby improving the effectiveness of instruction tuning and the generalization ability of fine-tuned models. Check out the Paper. If you like our work, you will love our newsletter.

Large Language Models 124

Large Language Models Data Quality LLM AI Researcher 124

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. On the Analyses tab, choose Data Quality and Insights Report.

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Machine Learning Data Quality ML Generative AI 82

Marktechpost

JANUARY 12, 2024

This increases the generalization loss forecasts for large-scale models and improves the accuracy of the ideal model or data scaling-up allocation approach. Impact of Data Quality – The best model or data scaling-up allocation approach has been heavily influenced by the caliber of the pre-training data.

Large Language Models 101

Large Language Models AI Modeling LLM Data Quality 101

Marktechpost

APRIL 1, 2024

Existing research emphasizes the significance of distributed processing and data quality control for enhancing LLMs. Utilizing frameworks like Slurm and Spark enables efficient big data management, while data quality improvements through deduplication, decontamination, and sentence length adjustments refine training datasets.

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Large Language Models ETL Data Ingestion Data Quality 85

Marktechpost

MAY 19, 2024

Differentially private synthetic data is synthesized by creating new datasets that reflect the key characteristics of the original data but are entirely artificial, thus protecting user privacy while enabling robust model training. Also, don’t forget to follow us on Twitter. If you like our work, you will love our newsletter.

Machine Learning 104

Machine Learning Large Language Models LLM AI 104

AI Weekly

MAY 11, 2023

dailywire.com Sponsor Access to World-Class AI/ML Programs from Top Universities Developing future-ready skills in artificial intelligence and machine learning are key to unlocking your career growth. Explore upcoming AI/ML courses from top global universities and join 250,000+ professionals taking their next step.

AI Chatbots 130

AI Chatbots Chatbots Robotics Artificial Intelligence 130

TheSequence

DECEMBER 3, 2023

Get all the contest details -> 🔎 ML Research GAIA Benchmark Researchers from Meta, HuggingFace, GenAI and AutoGPT published GAIA, a benchmark for general AI assistants. GPT Crawler A cool framework that can crawl a website and create a custom OpenAI GPT based on the data —> Read more.

AI Strategy 110

AI Strategy Generative AI DevOps Data Quality 110

Marktechpost

MAY 14, 2024

The success of models tuned with this dataset underscores the potential of web-mined instruction data to dramatically enhance the reasoning abilities of LLMs, broadening their application scope and setting new benchmarks for data quality and model performance in AI. Check out the Paper and Project.

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Large Language Models LLM Data Quality Algorithm 106