Best Practices for Building ETLs for ML
KDnuggets
OCTOBER 12, 2023
It delves into several software engineering techniques and patterns applied to ML. This article talks about several best practices for writing ETLs for building training datasets.
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KDnuggets
OCTOBER 12, 2023
It delves into several software engineering techniques and patterns applied to ML. This article talks about several best practices for writing ETLs for building training datasets.
KDnuggets
SEPTEMBER 20, 2023
On October 11th, 2023 the Feature Store Summit will bring together leading ML companies, such as Uber, WeChat and more, for in-depth discussions about data and AI.
KDnuggets
SEPTEMBER 27, 2023
A new way to do MLOps for your Data-ML-Product Teams.
KDnuggets
SEPTEMBER 19, 2022
This scholarship program aims to help people who are underserved and that were underrepresented during high school and college - to then help them learn the foundations and concepts of Machine Learning and build a careers in AI and ML.
Hacker News
NOVEMBER 14, 2023
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all - GitHub - microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
insideBIGDATA
APRIL 6, 2023
In this special guest feature, Gideon Mendels, CEO and co-founder of Comet ML, dives into why so many ML projects are failing and what ML practitioners and leaders can do to course correct, protect their investments and ensure success.
Machine Learning Research at Apple
NOVEMBER 7, 2022
Today, we are excited to release optimizations to Core ML for Stable Diffusion in macOS 13.1 Figure 1: Images generated with the prompts, "a high quality photo of an astronaut riding a (horse/dragon) in space" using Stable Diffusion and Core ML + diffusers running on-device on Apple Silicon.}> and iOS 16.2,
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.
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.
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?
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.
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.
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.
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.”
NOVEMBER 26, 2023
Amazon Redshift ML empowers data analysts and database developers to integrate the capabilities of machine learning and artificial intelligence into …
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…
KDnuggets
MAY 31, 2022
Add Layer to your existing ML code and quickly get a rich model and data registry with experiment tracking!
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.
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.
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.
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…
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
KDnuggets
NOVEMBER 30, 2021
The new platform provides a single API to abstract dozens of ML frameworks and databases.
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.
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.
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.
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.
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.
Towards AI
NOVEMBER 20, 2023
Last Updated on November 21, 2023 by Editorial Team Author(s): Amit Chauhan Originally published on Towards AI.
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
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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