Like with movies, I don’t have one favorite machine learning (ML) algorithm, but a few favorites, each for its own reason. Here are some of my top few algorithms and models: Most elegant: The ...

Reinforcement learning (RL) is a branch of machine learning that addresses problems where there is no explicit training data. Q-learning is an algorithm that can be used to solve some types of RL ...

Q-learning is arguably one of the most applied representative reinforcement learning approaches and one of the off-policy strategies. Since the emergence of Q-learning, many studies have described its ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Despite numerous innovations, the critical issue of optimizing UAV trajectories in unknown environments remains largely unaddressed. This paper introduces a novel approach, the Instructed ...

shenzhen, May 20, 2025 (GLOBE NEWSWIRE) -- Shenzhen, May. 20, 2025/––MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), announced that quantum algorithms will be deeply integrated ...

How do Machine Learning algorithms handle such large amount of data? This question was originally answered on Quora by Håkon Hapnes Strand. Subscribe To Newsletters. Subscribe: $1.50/week.

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.