testing 
Analytics Vidhya
APRIL 9, 2024
Introduction In this article, we will explore what is hypothesis testing, focusing on the formulation of null and alternative hypotheses, setting up hypothesis tests and we will deep dive into parametric and non-parametric tests, discussing their respective assumptions and implementation in python.
Analytics Vidhya
MARCH 21, 2024
Introduction In this article, we will explore what is hypothesis testing, focusing on the formulation of null and alternative hypotheses, setting up hypothesis tests and we will deep dive into parametric and non-parametric tests, discussing their respective assumptions and implementation in python.
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insideBIGDATA
NOVEMBER 20, 2023
But what is often overlooked is its ability to generate test scripts as well. Test scripts are susceptible to hallucinations just like code. In this contributed article, David Brooks, VP of products at Copado, discusses how much has been said about AI’s ability to generate code.
Analytics Vidhya
MAY 5, 2024
LLMs are typically trained on large datasets scraped from […] The post LLMs Exposed: Are They Just Cheating on Math Tests? These models are designed to process and understand human language, enabling them to perform tasks such as question answering, language translation, and text generation. appeared first on Analytics Vidhya.
Speaker: Timothy Chan, PhD., Head of Data Science
🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
KDnuggets
MAY 5, 2022
This brief overview of the concept of Hypothesis Testing covers its classification in parametric and non-parametric tests, and when to use the most popular ones, including means, correlation, and distribution, in the case of one sample and two samples.
Machine Learning Mastery
FEBRUARY 15, 2024
In the realm of inferential statistics, you often want to test specific hypotheses about our data. Using the Ames Housing dataset, you’ll delve deep into the concept of hypothesis testing and explore if the presence of an air conditioner affects the sale price of a house. Let’s get started.
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You can get new capabilities out the door quickly, test them with customers, and constantly innovate. Embedding analytics in your application doesn’t have to be a one-step undertaking. In fact, rolling out features gradually is beneficial because it allows you to progressively improve your application.
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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.
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Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.
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Assumptions mapping is the process of identifying and testing your riskiest ideas. A few simple ways to test if your assumptions are wrong. You'll learn: Why every product leader goes into a new project with untested, hidden assumptions. You'll learn: Why every product leader goes into a new project with untested, hidden assumptions.
Speaker: Tony Karrer, Ryan Barker, Grant Wiles, Zach Asman, & Mark Pace
Some takeaways include: How to test and evaluate results 📊 Why confidence scoring matters 🔐 How to assess cost and quality 🤖 Cross-platform cost vs. quality trade offs 🔀 and more!
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