Oct 22, 2025 · 6 min read · "Back when I worked in Customer Experience and the teammates and I were trying to understand NPS, this article would have been really helpful for us. It explains, with clear examples, what Population and Sampling mean, and how Confidence Intervals wo...
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Jun 11, 2025 · 5 min read · When it comes to conducting quality research, one critical decision can make or break the value of your study and your sampling design. This often-overlooked aspect of research methods is more than merely selecting a few participants or data points. ...
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Oct 8, 2024 · 2 min read · Once you’ve created a dataset, you want to explore the values inside. Exploring very large datasets can be difficult, as even simple operations can be expensive, both in terms of computational resources and time. The same sampling principle applies t...
Join discussionMay 24, 2024 · 9 min read · Recently, I was helping to improve the accuracey of an ML model in production and faced a difficult challenge. No matter what robust ML algorithm we selected or how we fine tuned the hyperparameters, the accuracy against real-world data just wouldn't...
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May 22, 2024 · 5 min read · Have you ever wondered how much data you really need for training your ML model? Determining the optimal sample size is a crucial step that can make or break your model's performance, computational efficiency and your project's time and costs. In thi...
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May 17, 2024 · 6 min read · Data is the lifeblood of machine learning models. The right data collection strategy can make all the difference. But how do you ensure that your data is representative, diverse, and unbiased? As a ML practitioner, it's crucial to understand the vari...
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Dec 25, 2022 · 2 min read · In statistics, different methods or techniques are used to obtain sample data from a given population. These methods or techniques are known as sampling techniques. Broadly, these can be classified into 4. They are: Random Sampling : As the name su...
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