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TikTok Researchers Introduce ‘Depth Anything’: A Highly Practical Solution for Robust Monocular Depth Estimation

AI NewsFebruary 6, 2024139Views 0Likes 0Comments

Foundational models are large deep-learning neural networks that are used as a starting point to develop effective ML models. They rely on large-scale training data and exhibit exceptional zero/few-shot performance in numerous tasks, making them invaluable in the field of natural language processing and computer vision. Foundational models are also used in Monocular Depth Estimation…

Solving Differential Equations With Neural Networks | by Rodrigo Silva | Feb, 2024

Data ScienceFebruary 6, 2024129Views 0Likes 0Comments

How Neural Networks are strong tools for solving differential equations without the use of training data Photo by Linus Mimietz on UnsplashDifferential equations are one of the protagonists in physical sciences, with vast applications in engineering, biology, economy, and even social sciences. Roughly speaking, they tell us how a quantity varies in time (or some…

Books, Courses, and Live Events to Learn Generative AI with O’Reilly

Data AnalyticsFebruary 5, 2024112Views 0Likes 0Comments

Image by Editor Generative AI is growing, with more people interested in how they can transition into the AI sector. A big hit at the moment and if you have clicked on this link, you are also wondering what you can do to learn more about Generative AI. In this blog, I will…

Meet CompAgent: A Training-Free AI Approach for Compositional Text-to-Image Generation with a Large Language Model (LLM) Agent as its Core

AI NewsFebruary 5, 2024114Views 0Likes 0Comments

Text-to-image (T2I) generation is a rapidly evolving field within computer vision and artificial intelligence. It involves creating visual images from textual descriptions blending natural language processing and graphic visualization domains. This interdisciplinary approach has significant implications for various applications, including digital art, design, and virtual reality. Various methods have been proposed for controllable text-to-image generation,…

Solving a Tennis Refactoring Challenge in Python using SOLID | by Tomer Gabay | Feb, 2024

Data ScienceFebruary 5, 2024134Views 0Likes 0Comments

A step-by-step illustration of how to use SOLID to solve a refactoring challenge Photo by Lucas Davies on UnsplashIntroduction Code refactor challenges are well-known by software engineers, but less so by data scientists, though data scientists can also highly benefit from practising such challenges. By practising these, especially when applying the SOLID principles, you learn…

A Data Lake, You Call It? It’s a Data Swamp

Data AnalyticsFebruary 5, 2024130Views 0Likes 0Comments

Image by Author If you’re a data professional, you’re probably familiar with the data lake architecture. A data lake can store large volumes of raw and unstructured data. So it offers both flexibility and scalability. That said, in the absence of data governance, a data lake can quickly turn into a “data swamp”…

Researchers from ETH Zurich and Microsoft Introduce EgoGen: A New Synthetic Data Generator that can Produce Accurate and Rich Ground-Truth Training Data for EgoCentric Perception Tasks

AI NewsFebruary 5, 2024112Views 0Likes 0Comments

Understanding the world from a first-person perspective is essential in Augmented Reality (AR), as it introduces unique challenges and significant visual transformations compared to third-person views. While synthetic data has greatly benefited vision models in third-person views, its utilization in tasks involving embodied egocentric perception still needs to be explored. A major obstacle in this…

Tagging Mountaineering Accident Reports Using bart-large-mnli | by Karla Hernández | Feb, 2024

Data ScienceFebruary 5, 2024126Views 0Likes 0Comments

I discovered the Himalayan Database a few weeks ago and decided to create a few “whimsical” visualizations based on this dataset. In two previous articles I created a simple elevation plot for Everest expeditions and a plot showing the relative number of deaths for 5 Himalayan peaks. This time I wanted to explore expedition accident…

Encoding Categorical Variables: A Deep Dive into Target Encoding | by Juan Jose Munoz | Feb, 2024

Data ScienceFebruary 5, 2024114Views 0Likes 0Comments

Data comes in different shapes and forms. One of those shapes and forms is known as categorical data. This poses a problem because most Machine Learning algorithms use only numerical data as input. However, categorical data is usually not a challenge to deal with, thanks to simple, well-defined functions that transform them into numerical values.…

Cropping Landsat Scenes from their Bounding Box using Python | by Conor O’Sullivan | Feb, 2024

Data ScienceFebruary 4, 2024143Views 0Likes 0Comments

Removing the outer border of Landsat satellite images using the stac file (source: author)Telling stories with satellite images is straightforward. The mesmerising landscapes do most of the work. Yet, visualising them takes some work such as selecting and scaling the RGB channels. In this article, we will go further. We will see how we can…