In a broader mathematical or computational perspective, an optimization problem is defined as a problem of finding the best solution from all feasible solutions. In terms of Machine Learning and…
Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs. Thinking of GNNs as PDEs leads to a new broad class of graph ML methods.
The best free & open-source vector graphics software allows you to enjoy creativity & easily create quality images that are ideal for detailed illustrations.
Written by Dheepan Ramanan (@dheepan_ramanan), Data Scientist and Ivan Kopas (@ivan_kopas), Machine Learning Engineer Last Friday ARK Invest released a new price target for Tesla as well as an updated, open-source model. The scale of autonomous ride hailing networks and ARK’s estimate for Tesla’s dominance emerged as the most contentious elements in the model. These components contribute nearly 50% of ARK’s $3k 2025 price target. On twitter there has been considerable debate on the size of the Robotaxi market and Tesla’s lead in autonomous driving, questioning whether Tesla’s Full Self Driving (FSD) approach can be reverse-engineered and replicated by the competitors.
For instance, you might learn in an online course how to run a YOLO network, but a real-world use case might asks for 7 YOLO networks in distributed GPUs and a HydraNet architecture. What the heck is…
Databases are the cornerstone of any Software Applications. You will need one or more databases to develop almost all kind of Software Applications: Web, Enterprise, Embedded Systems, Real-Time…
An introduction to what a Mesh, Shader and Material is in Unity, how to set Shader Properties from C#, a brief look at Forward vs Deferred rendering and some information about Material instances and Batching. HLSL | Unity Shader Tutorials, @Cyanilux
Let’s imagine a hypothetical situation. There’s an infection going round, and we want to predict the future severity of someone’s illness. There is a test that offers a good prediction. Let’s say the outcome of the test has a correlation of 0.78 with the patient's severity of infection. The problem with the test is that…
This blog post is going to be a little different to the previous few posts, there will be essentially no mathematics nor code. It is not intended as a how to or instructional post, merely a repository for my current opinions.
In this blog post we will cover some of the basics of the Barnes Hut algorithm. This is completely new to me, it is not an algorithm I’ve used/studied before (and I am by no means an astrophysicist). Nonetheless it has piqued my interest so I have decided to write about it. In this blog I will be talking about 2 dimensions unless otherwise stated, this just makes the resulting code run a little quicker and output easier to visualise. Modifying the 2d code to be 3d (or even higher dimension) requires only minor revisions.
In this blog post we will begin to look at Monte Carlo methods and how they can be used. These form the backbone of (essentially) all statistical computer modelling.
"In computer science, syntactic sugar is syntax within a programming language that is designed to make things easier to read or to express. It makes the language "sweeter" for human use: things can be expressed more clearly, more concisely, or in an alternative style that some may prefer." -- https://en.wikipedia.org/wiki/Syntactic_sugar
Cofnijmy się o jeden kroczek. Bo napisałam już ogólnie o machine learning. Napisałam również o klasyfikacji tekstu. Nie wspomniałam jednak ani słowem czym jest grupa ucząca, walidacyjna i testowa. A to przecież jedna z podstawowych informacji, które warto zrozumieć, kiedy zabieramy się za tematykę machine learning. Zwłaszcza, że przyda się nie tylko w przypadku klasyfikacji.
Any fundamental discovery involves a significant degree of risk. If an idea is guaranteed to work then it moves from the realm of research to engineering. Unfortunately, this also means that most…
Audio on Unix is a little zoo, there are so many acronyms for projects and APIs that it's easy to get lost. Let's tackle that issue! Most articles are confusing because they either use audio technical jargon, or because they barely scratch the surface and leave people clueless. A little knowledge can be dangerous.