Basic knowledge every data scientist should have. Reproducibility, data and model versioning, tracking machine learning experiments, documentation, testing.
A circular economy is an economic model that aims to minimize waste and maximize resource efficiency. As a Data Scientist in the Supply Chain Department, you can build simulation models to assess the…
Let's learn about Apache Flink and sentiment analysis by building a real-time sentiment analysis streaming application for the Twitch chat.
Imagine, you find yourself blindfolded in the center of a dense, unknown city. At each crossroad, flips of a coin decide your next steps: left, right, forward, or backward. With no vision to guide…
Visualization is a quick and effective way of getting insights from your data. This article provides a step-by-step guide for exploring a time series using graphics.
This walkthrough is about a paper that kicked off a new era of generative deep learning in computer vision and many other fields subsequently: the era of diffusion models. It’s titled “Denoising…
Figuring out where several 3D lines meet is really useful in fields like 3D Reconstruction or Augmented Reality. For instance, it helps us triangulate a 3D point from its multi-view 2D image…
This is a compilation of product data scientists interview questions at Lyft collected from all reviews on GlassDoor, with commentaries from real experience
This article explains how Large Language Models (LLM) like GPT can be customized. It gives non AI experts a basic and fun framework everyone can understand
Thanks to the release of Mixtral, the Mixture of Experts (MoE) architecture has become popular in recent months. This architecture offers an interesting tradeoff: higher performance at the cost of…