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My Easy Guide to Pre vs. Post Treatment Tests

A fast introduction to Before and After Tests with code.Gustavo Santos·FollowPublished inTowards Data Science·13 min read·2 hours ago--ShareI'll start this post by saying that A/B Testing was never a robust skill for me. “Okay,...

AI-driven tool makes it easy to personalize 3D-printable models

As 3D printers have change into cheaper and more widely accessible, a...

Reinforcement Learning: an Easy Introduction to Value Iteration

Solving the instance using Value IterationVI should make much more sense once we complete an example problem, so let’s get back to our golf MDP. We've formalised this as an MDP but currently, the...

3 Easy Ways To Compare Two Pandas DataFrames

Data ScienceQuickly learn tips on how to find the common and unusual rows between the 2 pandas DataFrames.It is a straightforward task — while you use built-in methods in pandas.In Python Pandas, a DataFrame...

An Easy Guide to Master Moving Average and Running Total in SQL

ScenarioSay, We now have a table named “ARTICLES” that captures day by day view counts for various articles from 1st June 2023 to tenth June 2023. Each entry within the table represents a date,...

AI-text detection tools are very easy to idiot

Daphne Ippolito, a senior research scientist at Google specializing in natural-language generation, who also didn't work on the project, raises one other concern. “If automatic detection systems are to be employed in education...

Data Evaluation Made Easy: Using LLMs to Automate Tedious Tasks How LLMs may help Examples of using LLMs Which LLM to make use of? Suggestions for using LLMs...

Let’s explore some examples of those to see just how powerful and versatile the tools are today.This section will contain examples of the appliance of LLMs. The examples are mostly indicated with a special...

Data Evaluation Made Easy: Using LLMs to Automate Tedious Tasks

Data evaluation may be equal parts difficult and rewarding. From cleansing messy datasets to constructing complex models, there’s all the time lots to do, and never enough time to do it. But what if...

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