Analytics Vidhya
AUGUST 6, 2024
But it […] The post Try GitHub Models: Test AI Models like GPT-4o and Llama 3.1 You want a place where you can not only store your code but also collaborate with others, keep track of changes, and maybe even show off your work to potential employers or developers. That’s where GitHub comes in!
Analytics Vidhya
SEPTEMBER 19, 2022
Introduction For data scientists and machine learning engineers, developing and testing machine learning models may take a lot of time. For instance, you would need to write a few lines of code, wait for each model to run, and then go on to […].
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Analytics Vidhya
JUNE 13, 2024
Introduction With the advancements in Artificial Intelligence, developing and deploying large language model (LLM) applications has become increasingly complex and demanding. LangSmith is a new cutting-edge DevOps platform designed to develop, collaborate, test, deploy, and monitor LLM applications.
Analytics Vidhya
NOVEMBER 16, 2023
Introduction A goal of supervised learning is to build a model that performs well on a set of new data. The problem is that you may not have new data, but you can still experience this with a procedure like train-test-validation split.
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
Analytics Vidhya
JANUARY 20, 2022
Table of contents Introduction Multilevel Models Advantages of Multilevel models When do we use Multilevel Models Types of Multilevel Model Random intercept model Random coefficient model Hypothesis testing: Likelihood Ratio Testing End-Note Introduction Suppose, you have a dataset of faculty salaries of a university […].
Analytics Vidhya
OCTOBER 17, 2022
In the previous articles, we have gone through the introduction, MLOps pipeline, model training, model testing, model packaging, and model registering. We have seen how to train, test, package, and register […]. Introduction This article is part of blog series on Machine Learning Operations(MLOps).
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Every sales forecasting model has a different strength and predictability method. It’s recommended to test out which one is best for your team. This way, you’ll be able to further enhance – and optimize – your newly-developed pipeline. Your future sales forecast? Sunny skies (and success) are just ahead!
Speaker: Gertjan de Lange
If the last few years have illustrated one thing, it’s that modeling techniques, forecasting strategies, and data optimization are imperative for solving complex business problems and weathering uncertainty. Experience how efficient you can be when you fit your model with actionable data. Don't let uncertainty drive your business.
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How to test AI ASR solutions. How to improve model accuracy with training data. Get the information you need to ensure your evaluation experience is efficient and yields the data you need to make your purchasing decision. Download our solution brief now.
Speaker: John Cutler, Product Evangelist and Coach at Amplitude
Even brick and mortar businesses are integrating more digital approaches to CX -- testing out loyalty programs and subscription-based models. How product data can optimize your subscription and loyalty models. The reality is that with the new wave of digital considerations, navigating expansion can be a tricky subject.
Speaker: Teresa Torres, Internationally Acclaimed Author, Speaker, and Coach at ProductTalk.org
As a result, many of us are still stuck in a project-world rut: research, usability testing, engineering, and a/b testing, ad nauseam. These methods are better than nothing, but how can we improve on this model? Data shows that the best product teams are shifting from this mindset to a continuous one.
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Download this whitepaper to learn about: Development of AI standards for pandemic models that will be used in future pandemic responses. Enablement of swift and safe innovation in rapid antigen tests. Modernization of U.S. health reporting standards.
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