Tag: Solving

We will begin with perhaps the most basic variation on the Gaussian integral: Where a > 0. While the method for solving this integral will be the exact same as the standard Gaussian integral, I wanted to cover this since I will be using the result for the other integrals. All w...

AI experts should not get offended when AGI researchers complain about the inadequacies of deep learning. Nobody is really out to get rid of DL. While it is true that the advent of AGI will render DL obsolete in some fields, we believe that it will probably continue to be useful for many automation ...

Given a requirement, sometimes multiple alternatives may be available to implement it. In this blog we look at a practical use case for positioning text in Compose. We’ll analyze multiple alternatives to solve it, using different Compose text APIs. We’ll review pros and cons and, as a bo...

Imbalanced classification is a common problem in machine learning, particularly in the realm of binary classification. This occurs when the training dataset has an unequal distribution of classes, leading to a potential bias in the trained model. Examples of imbalanced classification problems includ...

The Three Jugs Problem is a classic puzzle that challenges your ability to measure a specific quantity of water using three jugs of different capacities and a faucet. In this technical blog, we’ll delve into the problem formulation and explore a strategy to solve it. Problem Formulation ...

This is the fourth article in a series on using large language models (LLMs) in practice. Here, I will discuss prompt engineering (PE) and how to use it to build LLM-enabled applications. I start by reviewing key PE techniques and then walk through Python example code of using LangChain to...