Artificial intelligence is among the fastest-growing industries. The number of open-source ML libraries to which the best programmers contribute new features and functionalities is constantly increasing. With fast-paced advances in machine learning, some ML frameworks and libraries become outdated after a certain period of use. …

ChatGPT, a chatbot capable of conducting conversations in a human-like manner, has made headlines both in specialized technology publications and mainstream news. Some experts predict that this marks the beginning of a new era in AI. …

The genie you wish you had in your pocket. — Generative artificial intelligence has seen an incredible popularity surge in 2022. Big Think has called it ‘the technology of the year’, and judging from the amount of attention and VC support generative AI startups have been gaining this year, this claim is more than justified. …

K-means is a data clustering approach for unsupervised machine learning that can separate unlabeled data into a predetermined number of disjoint groups of equal variance — clusters — based on their similarities. It’s a popular algorithm thanks to its ease of use and speed on large datasets. In this blog…

Despite being vital to machine learning, feature engineering is not always given due attention. Feature engineering is a supporting step in machine learning modeling, but with a smart approach to data selection, it can increase a model’s efficiency and lead to more accurate results. …

Machine learning and artificial intelligence is a field that drives major innovations across different industries. It is predicted that in 2023, the AI market will reach $500 billion, and in 2030, $1,597.1 billion in size. …

Stable Diffusion has been a buzzword in the last months after it was publicly unveiled by its developer Stability AI on August 22, 2022. Not only Stable Diffusion generates complex artistic images based on text prompts, but it’s also an open source image synthesis AI model available to everyone. …

Training machine learning models requires a lot of data, which is not always available. This is where transfer learning comes into play as it leverages previously trained models. In this blog post, we’ll explore the definition, methodology, benefits, and applications of transfer learning. …

The support vector machine (SVM) algorithm is a machine learning algorithm widely used because of its high performance, flexibility, and efficiency. In most cases, you can use it on terabytes of data, and it will still be much faster and cheaper than working with deep neural networks. The algorithm is…