Search Results for "computer based training"

Hiring-without-whiteboards is a curated list of companies and teams that avoid traditional "whiteboard" interviews, instead focusing on realistic and practical evaluation methods. In this context, "whiteboards" symbolizes outdated or unhelpful computer science trivia questions often criticized in technical interviews. The project highlights organizations that emphasize interviewing techniques more aligned with actual day-to-day work, such as collaborative problem-solving, pair programming, or take-home assignments. It encourages a shift away from brainteasers, riddles, or puzzle-based interviews, which can create unnecessary barriers for candidates. ...

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp. It's a high-performance alternative API to whatzapp, you can send, text messages, files, images, videos and more. Remember, the API was developed on a platform called RESTful Web services, providing interoperability between computer systems on the Internet. ...

...It consists of a curated set of tasks where models must infer patterns from input-output examples and apply those rules to new unseen cases, without relying on memorization or prior training data. The dataset is structured as grid-based puzzles, where each task requires understanding transformations such as symmetry, counting, or spatial manipulation. Unlike traditional machine learning benchmarks, ARC emphasizes generalization and reasoning over statistical pattern recognition, making it particularly challenging for current AI systems. ...

Face-Detection-JavaScript is a small browser-based computer vision demo that uses JavaScript and face-api.js to analyze live webcam video. It loads face detection, facial landmark, face recognition, and facial expression models from a local models folder. Once the webcam stream starts, the app creates a canvas overlay and draws detection results directly over the video feed. It can identify face boxes, map facial landmark points, and display detected expressions in near real time. ...

The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The...

ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. ...