The relationship between bias and variance is similar to overfitting and underfitting in machine learning. Learn how to achieve optimal model performance by keeping in mind the bias-variance tradeoff.
The number of open-source ML libraries is constantly increasing, but which ones should you use in your project? In this blog post, we present fifteen libraries to pay attention to in 2023.
Multimodal learning is a machine learning technique that incorporates data from multiple modalities – ways of perceiving the world – to create models that have increased accuracy and better capabilities.
ChatGPT, a chatbot capable of conducting conversations in a human-like manner, has made headlines both in specialized technology publications and mainstream news.
Generative AI has recently seen an incredible popularity surge. In this post, we take a closer look at what it is and how it works, as well as outline common use cases and perspectives for the future.
K-means is an algorithm that can separate unlabeled data into a predetermined number of clusters. In this blog post, we look at its underlying principles, use cases, as well as benefits and limitations.
Feature engineering is the process of designing predictive models based on a carefully selected set of data. Read our step-by-step guide on how to introduce feature engineering into your model.
In this interview, we speak with Dr. Yuriy Gankin and Maxim Kazanskii from Quantori – a data science and digital transformation company specializing in research and development in the biopharma industry.
Stable Diffusion is a free, open-source neural network for generating photorealistic and artistic images based on text-to-image and image-to-image diffusion models. Read our tips to start generating your own masterpieces in minutes.
In this blog post, we explore the definition, methodology, benefits, and applications of transfer learning. We also discuss various transfer learning strategies and provide a selection of pre-trained models.
The support vector machine (SVM) algorithm is a machine learning algorithm widely used because of its high performance, flexibility, and efficiency. Learn more about it in our article.
The most popular solutions for storing data today are data warehouses, data lakes, and data lakehouses. This post gives a detailed overview of these storage options and their pros and cons for specific purposes.
The k-nearest neighbors (kNN) algorithm is a simple tool that can be used for a large number of real-world problems. In this article, we cover what kNN is, how it works, and how to implement it in machine learning projects.