Classifier

OpenAI’s AI Text Classifier is no longer available. The tool failed to accurately classify whether a human or AI wrote submitted text, the company confirmed. Page not found. The classifier page now shows a “Page Not Found – We couldn’t find the page you were looking for” message, rather than the tool. What happened. OpenAI added a note to the original blog post announcing the AI Text Classifier: “As of July 20, 2023, the AI classifier is no longer available due to its…

In the world of e-commerce, product reviews are essential for fostering client trust and loyalty. However, manually reading through tens of thousands of user evaluations to identify recurring themes and sentiments may be a time-consuming and daunting endeavor. Here comes the role of automatic product classifiers. Using machine learning techniques, an automated product classifier may categorize user reviews based on specified categories or feelings. In this blog article, we will discuss the process of developing an…

Gain insight into the fundamental processes involved in building a decision tree classifier from the groundPhoto by Jeroen den Otter on UnsplashDecision trees serve various purposes in machine learning, including classification, regression, feature selection, anomaly detection, and reinforcement learning. They operate using straightforward if-else statements until the tree’s depth is reached. Grasping certain key concepts is crucial to fully comprehend the inner workings of a decision tree.Two critical concepts to grasp…

From two different perspectives and with 3 roundsEven though we can find many posts and articles talking about this question, I decided to add one more. Because it is an opportunity to discuss some underlying theories and frameworks.Some people try to defend their viewpoints by giving a firm answer: logistic regression is a regressor, or logistic regression is a classifier. I will not defend a viewpoint, because the debate is kind of absurd to me.For those defending that logistic regression is a classifier, please, you…

An Instructional Guide and Flow Diagram for Building a Supervised Machine Learning Text Classifier in PythonPhoto by Patrick Tomasso on UnsplashLet’s cut to the chase. There are a lot of steps involved in building a text classifier and understanding the world of Natural Language Processing (NLP). These steps have to be implemented in a specific order. There are even more steps required if the target class in the data is imbalanced. Learning this all from scratch can be a bit of a minefield. There are plenty of learning…

OpenAI, the artificial intelligence company behind viral text-generator ChatGPT, has released a new AI tool intended to help manage the mess wrought by its previous creation. Unfortunately, it’s not very good. The company announced a free web-based AI-detection widget on Tuesday. The application is intended to classify text samples based on how likely they are to have been generated by artificial intelligence vs. written by an actual person. Given a sample of text, it spits out one of five possible assessments: “Very…

Building an image classifier the practical way (based on a true story)Photo by Elena Mozhvilo on UnsplashMost practitioners first learn deep learning through the lens of image classification. If you’ve taken a programming course, then consider this to be the equivalent of the “hello world” exercise they give you at the start. While many experts say image classification is solved (and there may be some truth in that), there’s a lot of nuance and craft you can learn from this type of problem. With that being said, over the…

From theory to practice with Bayes TheoremPhoto by Joel Abraham on UnsplashMath and Physics are full of theorems, equations, principles, axioms, and corollaries. When I started studying Physics I remembered I got to the point where all the courses I studied had the same structures:A. Defining the fundamental assumptions B. Using math to build the next “brick of the wall”C. Stacking one brick on top of the other until the whole pieces come together into an elegant, beautiful, model of a portion of the worldLet’s take the…

A practical example implemented in MathematicaThe US Navy using the Mark I Perceptron to read letters. National Museum of the US Navy, 1960. Image from Wikimedia Commons (Public Domain).The Rosenblatt Perceptron, developed by Frank Rosenblatt in 1958, is considered the origin of neural networks because it was the first algorithm that demonstrated the ability of a machine to learn from data.The Perceptron was a simple model that consisted of a single layer of artificial neurons, or units, that could be trained to recognize…

Conformal Prediction in Julia — Part 2Conformal Predictions sets with varying degrees of uncertainty. Image by author.Deep Learning is popular and — for some tasks like image classification — remarkably powerful. But it is also well-known that Deep Neural Networks (DNN) can be unstable (Goodfellow, Shlens, and Szegedy 2014) and poorly calibrated. Conformal Prediction can be used to mitigate these pitfalls.In the first part of this series of posts on Conformal Prediction, we looked at the basic underlying methodology and…