Just as birds of the same feather flock together, data points in a dataset with similar characteristics tend to cluster together. This is the fundamental idea behind the K Nearest Neighbors (KNN) algorithm, a popular and intuitive method used in machine learning. This blog post aims to explain KNN in a way that is accessible and understandable for everyone. What is K Nearest Neighbors? K Nearest Neighbors, or KNN, is a supervised machine learning algorithm that classifies a data point based on how its neighbors are classified. To illustrate, imagine you're trying to understand a person's character. One way you might do this is by looking at their friends or the group they hang out with. If most of their friends are athletes, you might classify this person as an athlete too. This is similar to how KNN works. However, KNN is considered a lazy learning algorithm, meaning it doesn't immediately generalize from the training data. It waits until it is given a test observati...

  (serve robotics delivery bot on delivery) Imagine, if you will, the bustling streets of Freetown, Sierra Leone. The vibrant markets, the lively chatter, the aroma of freshly cooked street food filling the air. Now, picture a small, autonomous robot navigating its way through the crowd, carrying a delivery from your favorite restaurant. Sounds like a scene from a science fiction movie, right? Well, this is already a reality in Los Angeles, USA, thanks to a partnership between Uber Eats and Serve Robotics. The AI-Powered Delivery Revolution In LA, up to 2,000 of these AI-powered robots have been deployed to serve customers. Each robot is equipped with advanced AI models that allow it to understand its surroundings, navigate the city streets, and avoid obstacles. This technology is the result of years of research and development, and it's changing the game for food delivery services. The Robots in Action (Customer doing a pickup) Each robot can travel at a speed of up to seven...

  Hello, AI enthusiasts! Today, we're diving into the fascinating world of Transformers - not the shape-shifting robots, but a revolutionary architecture in machine learning that has transformed (pun intended) natural language processing. This blog post is aimed at beginners, so don't worry if you're new to the field. We're going to break it down step-by-step! What are Transformers? Transformers are a type of model architecture used in the field of deep learning, specifically for tasks involving natural language processing (NLP). Introduced by Vaswani et al. in a paper titled "Attention is All You Need" (2017), Transformers have achieved impressive results in a wide range of NLP tasks, such as translation, text summarization, and sentiment analysis.  Why 'Transformers'? The secret sauce of Transformers lies in their unique ability to 'transform' input data (like text) into meaningful output (like a translation or summary), thanks to the...