Unsupervised Clustering: Can We Identify Clusters in the Descriptions of Sounds in Music?
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. The data used is tricky because it is a list of Spotify songs, which are assigned values that describe the sounds in them. At this point, the goal is to see if those descriptions …
How To Use Target Encoding in Machine Learning Credit Risk Models — Part 1
Author(s): Varun Nakra Originally published on Towards AI. Target encoding, also known as mean encoding or likelihood encoding, is a technique used to convert categorical variables into numerical values based on the target variable in supervised learning tasks. This method is particularly …
Deep Exploratory Analysis and Random Forest Classification
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. Decision tree types of classification algorithms have the advantage that they produce results that are relatively easier to explain in terms of the impact of the predictors when compared to other supervised training algorithms, …
Use of Pretrained BERT to Predict the Rating of Reviews
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. BERT is a state-of-the-art algorithm designed by Google to process text data and convert it into vectors (https://en.wikipedia.org/wiki/BERT_(language_model) . These can then by analyzed by other models (classification, clustering, etc) to produce different analyses. …
Web scraping & NLP
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. In this example, I extract data from a Wikipedia list of the most grossing movies go into each of the links and fetch the text of the movie’s article. Then I use BERTopic (which …
Quick and Easy Application of Network Graph Analysis: Measure Connectivity Between Countries by Air Traffic
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. I use the Networkx package to analyze a set of air routes between a group of countries and describe how they are connected. Networkx is documented in the following publication: Aric A. Hagberg, Daniel …
Descriptive Analysis
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. Descriptive analytics is a big part of working with data, it could be before more complicated tasks, such as machine learning or on its own. In this example I illustrate the use of deep …
Low-Rank Adaptation (LoRA): From Intuition to Implementation to Interview Questions
Author(s): Harsh Maheshwari Originally published on Towards AI. Delving Deeper into LoRA for LLMsPhoto by Digital Content Writers India on Unsplash LLM are getting larger and larger each day, recently, Meta has announced that they are currently working on the 400b Llama …
Using NLP (Doc2Vec) and Neural Networks (with Keras): Removing Hate Speech and Offensive Tweets
Author(s): Greg Postalian-Yrausquin Originally published on Towards AI. This is a great example of how more than one ML step can be used to achieve a goal. In this exercise, I will combine NLP (Doc2Vec) with binary classification to extract offensive and …
Synthetic Data Generation in Foundation Models and Differential Privacy: Three Papers from Microsoft Research
Author(s): Jesus Rodriguez Originally published on Towards AI. Created Using Ideogram I recently started an AI-focused educational newsletter, that already has over 170,000 subscribers. TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. …
Satellite Image Classification with Machine Learning & Python — Part 1: Creating Model and Classifying
Author(s): KokaTic Originally published on Towards AI. Study region of our tutorial — El Oued, Algeria (source: Bing maps) Image classification is a pivotal task in the realm of machine learning, particularly within the domain of remote sensing. In this series, we …
Perfect Answer to Deep Learning Interview Question — Why Not Quadratic Cost Function?
Author(s): Varun Nakra Originally published on Towards AI. One of the most common question asked during deep learning knowledge interviews is — “Why can’t we use a quadratic cost function to train a Neural Network?”. We will delve deep into the answer …
The Brief History of Binary Images
Author(s): Radmila M. Originally published on Towards AI. Photo by Etienne Steenkamp on Unsplash Introduction Binary images might be called as the simplest form of images that can take on two values — black and white, or 0 and 1. Basically, a …
How Do Diffusion Models Work? Simple Explanation: No Mathematical Jargon, Promised!
Author(s): Suhaib Arshad Originally published on Towards AI. Background Knowledge Essentially, there are 3 common types of generative models: Generative Adversarial Networks (GANs), Variational Autoencoder, and Flow-based models. Although they have proven their spot as high-quality image-generating models, they fall short on …
Fueling (literally) the AI Boom
Author(s): Aneesh Patil Originally published on Towards AI. Photo by NASA on Unsplash Let’s take a moment to step back in time to our 5th-grade selves, a nostalgic #Throwback____ (insert today’s date) if you will. Picture ourselves in science class, perhaps doodling …
Popular posts
Updates
Recent Posts
