Towards Data Science

Image by Author. When one mentions “ML monitoring,” this can mean many things. Are you tracking service latency? Model accuracy? Data quality? The share of visitors that click on the … Read more

Build an object detection model, compare it to intensity thresholds, evaluate it and explain it using DeepSHAP (source: author) If the world was less chaotic self-driving cars would be simple. … Read more

We explore the limits of what vision-language models get about language in our Oral Paper at ICLR 2023 Photo by ThisIsEngineering. Multimodal AI is the talk of the town. With … Read more

A Step-by-Step guide on how to conduct a structured root cause analysis In my previous article, I discussed how to define activation metrics for your business — those metrics that … Read more

Svelte Bar Chart (source: author, 2023) Creating interactive bar chart with Svelte Data visualisation draws insight to what lives in our data. The usual way is to make graphs or … Read more

Photo by CDC on Unsplash In this post I’m going to review a recent paper in the interface between medicine research and modeling and machine learning. The paper, Green, A.G., … Read more

A few canonical and research-proven techniques to adapt large language models to domain specific tasks and the intuition of why they are effective. Source: https://unsplash.com/ Ever since being popularized by … Read more

A Python implementation of Q-learning to solve the Taxi-v3 environment from OpenAI Gym in an animated Jupyter Notebook Photo by Alexander Redl on Unsplash The goal of the Taxi Environment … Read more

A paradigm shift ASCII art of a puppy produced by the author using ChatGPT. Artificial intelligence (AI) has advanced incredibly fast in recent years, giving rise to powerful tools known … Read more

Using LLMs to obtain labels for supervised models Photo by h heyerlein on Unsplash Labeling data is a critical step in building supervised machine learning models, as the quantity and … Read more

A digestible introduction to how quantum computers work and why they are essential in evolving AI and ML systems. Gain a simple understanding of the quantum principles that power these … Read more

Better approaches to making statistical decisions Photo by Rommel Davila on Unsplash In establishing statistical significance, the p-value criterion is almost universally used. The criterion is to reject the null … Read more

Coffee Data Science Cutting up the shot to learn something new Coffee extraction happens over time, and it changes throughout an espresso shot. To better understand this, people have used salami … Read more

Take advantage of the distributive power of Apache Spark and concurrently train thousands of auto-regressive time-series models on big data Photo by Ricardo Gomez Angel on Unsplash 1. Intro Suppose … Read more

To even better understand Gradient Boosting Continue reading on Towards Data Science » Favorite

To boost performance, we implement a forgetful bloom filter and a custom Spark state store provider Photo by Leora Winter on Unsplash, Shippagan, NB, Canada This is the 5th article … Read more

From two perspectives to gain a better understanding of the linear models In this article, we will discuss this viewpoint: Polynomial regression is a linear regression. Photo by Denny Müller … Read more

Photo by Greyson Joralemon on Unsplash Five Tips for Writing Clean, Efficient and readable Code in PyTorch Introduction In the field of data science and programming in general, it is … Read more

Leveraging Large Language Models for Advanced NLP How to Use State-of-the-Art Models for Accurate Text Classification Photo by Jonathan Cooper on Unsplash This project aims to build a model capable … Read more

Improving Hebrew Q&A Models via Intelligent Prompting DALL-E 2: “A robot dressed in a robe writing biblical sentences in Hebrew. Digital art.” Hi all, I am sharing a short project I … Read more

Google's new model is trained to answer medical questions. How? Continue reading on Towards Data Science » Favorite

A summary of dataset distribution techniques for Federated Learning on the CIFAR benchmark dataset Federated Learning (FL) is a method to train Machine Learning (ML) models in a distributed setting … Read more

A review of recent trends, use cases and technologies Photo by Nghia Le on Unsplash Everyone is talking about machine learning. And this is not just a feeling: if you … Read more

How can salt help you with experiments? Photo by Manuel Asturias on Unsplash AB testing is one of the most well-known methods to measure the effect of new features’ implementation. … Read more

Could help to blend machine learning with classical approaches to sciences and engineering, by providing more interpretable models rooted in fundamental concepts Figure created by the author by combining different … Read more

My MLOps tutorials: [I will be updating this list as I publish articles on the subject] In the previous tutorial, we defined MLOps as a way to design, build, and … Read more

Easily train a Robotic Manipulator to avoid obstacles by using the robotic-maninpulator-rloa framework Photo by David Levêque on Unsplash The purpose of this article, beyond explaining how to train a … Read more

How to considerable reduce training time changing only 1 line of code Photo by Markus Winkler on Unsplash Introduction With the Intel® Extension for Scikit-learn package (or sklearnex, for brevity) … Read more

Start Your Coding for Computer vision with Python Photo by Dan Smedley on Unsplash Motivation We, human beings, perceive the environment and surroundings with our vision system. The human eye, … Read more

Scalable and equivariant spherical CNNs by DISCO convolutions No existing spherical convolutional neural network (CNN) framework is both computationally scalable and rotationally equivariant. Continuous approaches capture rotational equivariance but are … Read more

Behind the Hype — Understanding what ChatGPT can do and what it cannot do, is critical to make the most of the technology. A recent research paper from the Center … Read more

With the aid of convolutional neural networks and transfer learning, it is possible to build a classifier in determining whether solar panels are clean or dusty Photo by Moritz Kindler … Read more

Systematically resolve data issues in production Photo by Pavan Trikutam on Unsplash At any company, one of the best ways to gain and retain customers is to deliver excellent services, … Read more

A quick and simple demo for running DAGs on Airflow Photo by Kelly Sikkema on Unsplash Apache Airflow is quite popular in the data science and data engineering space. It … Read more

Opinion Is GPT-4 the next big step in AI we were all waiting for? Image generated by Stable Diffusion Today, I woke up, and the hashtag #gpt-4 was trending on … Read more

TDS Special Feature Expanding cities and a shrinking countryside Image from Unsplash, created by Louis Reed Are you a city dweller? You’re not alone! Our global urban population has reached … Read more