Abstract: In this paper, we propose a personalized seizure detection and classification framework that quickly adapts to a specific patient from limited seizure samples. We achieve this by combining two novel paradigms that have recently seen much success in a wide variety of real-world applications: graph neural networks (GNN), and meta-learning. We train a Meta-GNN based classifier that learns a global model from a set of training patients such that this global model can eventually be adapted to a new unseen patient using very limited samples. We apply our approach on the TUSZ-dataset, one of the largest and publicly available benchmark datasets for epilepsy. We show that our method outperforms the baselines by reaching 82.7% on accuracy and 82.08% on F1 score after only 20 iterations on new unseen patients.

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. To learn more about PyCaret, you can check the official website or GitHub.

Neural Networks (NNs), or Artificial Neural Networks (ANNs), started as a big promise, and their models were quite simple compared to the models we have today: it was a simple neuron with binary outputs based on thresholds. In layman terms, it would read values as input, sum them weighted by parameters (called learning weights, where the knowledge is stored), and compared to a threshold: if it is higher, the output is one (it simulated the firing of a neuron in biology, which follows similar patterns). Except for the big hope people placed on them, they could, and still, can only separate binary boundaries: yes or no, sick or no, guilty or no. Nonetheless, do not fall prey to the common trap that simplicity as being easy: boundaries can be hard even for complex decision processes, such as release or not a patient under healthcare, or release or not a prisoner after some appeals to do so. From one side, we had some people from neuroscience seeing on the models possible explanations for their biological phenomena (i.e., in silico simulations, it was quite appealing that we could simplify the brain workings using such a simple model, based on summations). On the other hand, applied mathematical and computer scientists looking for new solutions for their complex problems out of the box (e.g., XOR problem[1], it is a problem simple for humans, but hard for machines).

Data Science and Artificial Intelligence are two of the most popular and in-demand fields in the tech industry today. As more and more businesses adopt data-driven decision making, the demand for Data Scientists continues to grow. And as Artificial Intelligence technology becomes more sophisticated, the demand for AI experts is also on the rise. If you're interested in a career in Data Science or AI, you may be wondering what the difference is between these two fields. Data science is all about extracting knowledge and insights from data.

Google researchers believe that natural language processing and AI will enable robots to create their code to take action against new instructions. Google is currently testing a system that allows robots to write their code, follow instructions, and complete tasks. This is a way to streamline reprogramming policies for every new task. It can be tedious and time-consuming, and it requires domain experts. Staff could interact with robots on smart factory floors using simple commands without needing to write complicated code. Google researchers developed language modeling programs called Code as Policies (CaP). This code-writing AI system can generate new code for new instructions. Google robotics scientists stated in a blog post that “Given natural languages, instructions, current language models can write not only generic code, but, as we have discovered, code capable of controlling robot actions.” Google researchers have combined large language models with everyday robots to better respond to complex and abstract human requests. According to the Google team, CaP will enable a single system

Strap yourself in: Programming Artificial Intelligence is about to click! Since making the official tutorials for Bolt on Unity's Learn Site, creating this course has been a dream of mine. In collaboration with Holistic3D, I took Penny's quintessential C# tutorial series The Beginner's Guide to Artificial Intelligence and adapted it to *drumroll*… Unity Visual Scripting! In this course, you're getting the best of both worlds: Learning content from a renowned expert on AI and computer science remixed, reconfigured, and riffed on by a creative artist and designer who has helped thousands learn visual scripting from the early years to today… that's me! Through an open-ended, practice based approach you will follow along as each step is revealed for you to recreate two game worlds created with Unity 2021.3.9

The human mind can get really complicated at times. That's when we turn to meditation, taking deep breaths to forget all the chaos. It gives us certain fulfilment--by bringing out new traits of understanding and empathy--sometimes by not doing anything at all. What if machines could also meditate or do nothing for a day or two--to learn better? As absurd as it may sound, a group of researchers have now discovered how artificial neural networks can mimic sleep patterns of the human brain, boosting their utility across a spectrum of research areas.

This time of year, all the cute Christmas decor and ornaments are out, which makes trips even more fun. Shopping on its website isn't as fun, sadly, but it's still packed full of holiday sales. Target's Black Friday and Cyber Monday deals have been live for almost every day of the month, but several discounts are even sweeter now. Updated on November 26, 2022: We've added some navigation, the Bose QC Earbuds, and checked over the entire post. We test products year-round and handpicked these deals. Products that are sold out or no longer discounted as of publishing will be crossed out . We'll update this guide throughout the Black Friday and Cyber Monday weekend. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. The retailer is offering a price match guarantee this season. If you purchase an item in-store or online from now through December 24 and the price goes lower, you can request a price match.

The most shopped-for items or brands during Black Friday aren't that hard to guess. You could probably rattle off five without seeing a crumb of data -- just based on vibes alone. TVs, Apple products, and Roombas probably came to mind, and those were top of mind for Mashable readers on Black Friday itself, too. All three of those categories ranked in the top 25 most popular items at two of the biggest Black Friday retailers: Amazon and Walmart. Other expected synchronicities included non-iRobot robot vacuums and laptops.

The accelerating adoption of cloud computing, artificial intelligence/machine learning (AI/ML) solutions, and data analytics tools enables …