Hello, dear Sigmaritans! We all know that nowadays music is everywhere. It unites people and projects the most beautiful memories. Because music captures people's emotions, the Sigmoid team is developing a new project, Calliope, in which it comes to present the varied range of songs found in the team's playlist.
Hello, cherished Sigmaritans! Congratulations to the new generation of Sigmaritans! 🎉 Our latest examination showed the remarkable progress and knowledge acquired during the past 5 months of mentorship. Each Padawan had the opportunity to demonstrate their skills and tackle real-world ML tasks under the guidance of experienced mentors. Here are some
Exciting news! We're thrilled to announce a new era for our organization with updates to our board of directors for each department. We're so excited to welcome our new Sigmoid Director, Vladimir Stojoc, and believe that his leadership will take us to even greater heights. Let's all come together to
Hello, dear Sigmaritans! We're thrilled to announce that our team from Sigmoid will be participating in the Bosch Autonomous Self-Driving Championship! This competition, organized by the Bosch Research and Technology Center, challenges teams to develop cutting-edge technologies for autonomous vehicles. Our team is made up of experts in a variety
Hello, dear Sigmaritans! Data Science is the field of applying advanced analytics techniques and scientific principles to extract valuable information from data for business decision-making, strategic planning, and other uses. Further below we gathered the top 3 ways data science has improved the world: 1. Healthcare In healthcare, Data Science
Hello, dear Sigmaritans! The number of jobs in Artificial Intelligence continues to grow as more and more companies take the digital route. A career in technology has several benefits and a high salary is one of them. There are several exciting opportunities in the technology field, but today we are
Hi, cherished Sigmaritans! We all know that reading is the way to knowledge. Books will always remain those primary learning tools. The Sigmoid team comes to recommend 3 books about the field of Artificial Intelligence that you can add to your collection. 1. "Artificial Intelligence Basics: A Non-Technical Introduction" by
Artificial Intelligence is a theory and development of computer systems that can perform tasks that usually require human intelligence. Speech recognition, decision-making, and visual perception are, for example, features of human intelligence that Artificial Intelligence may possess. Humans can learn as they go along — in other words, learn from experience.
Hello, dear Sigmaritans! Have you ever asked yourselves why Artificial Intelligence is so popular? AI allows you to process large amounts of data in a way that would be difficult to do by a human. AI processes information with automated machine learning, like identifying and describing objects in images or
Hello, cherished Sigmaritans! Are you ready to expand your playlist and improve your knowledge regarding Artificial Intelligence? If that is the case, continue reading our recommendations on Top 3 TED Talks about Artificial Intelligence. 1. Understanding Artificial Intelligence and Its Future - Neil Nie Neil Nie’s performance on TED
Artificial Intelligence (AI) is the intelligence exhibited by machines, as opposed to the natural intelligence exhibited by animals, including humans. The term “Artificial Intelligence” was previously used to describe machines that mimic and demonstrate “human” cognitive abilities related to the human mind, such as “learning” and “problem-solving”. This definition has
Artificial intelligence is the ability of machines to perform certain tasks, which need the intelligence showcased by humans and animals. This definition is often ascribed to Marvin Minsky and John McCarthy from the 1950s, who were also known as the fathers of the field. When and where did it start?
The advancements in the Artificial Intelligence Field are being made very quickly. Every three months, the speed of Artificial Intelligence computation doubles, according to Stanford University’s 2019 AI Index report. Consequently, in the last five years, the field of Artificial Intelligence has made major progress in almost all its
Artificial intelligence (AI) refers to the simulation of human intelligence in machines programmed to think like humans and mimic their actions. As time passes and technology evolves, many more ways to use Artificial Intelligence are invented. Some of the best-known examples where we can find AI are the search engines
What is JensenShannonSelector ? JensenShannonSelector is a feature selector in kydavra that chooses feature columns based on the Jensen-Shannon divergence. It measures the similarity between two probability distributions. How to calculate Jensen-Shannon divergence ? It is based on the Kullback-Leibler divergence with the difference that it is symmetric and has a finite
Sometimes it is necessary to select some features from a dataset that are quite similar to a target column. One way is to compare the features with the target using divergence. One such divergence is the Bregman divergence. Kydavra implements a selector based on Bregman divergence named BregmanDivergenceSelector. What is
What is ItakuraSaitoSelector? It is a selector that is based on Itakura-Saito divergence, which measures the difference between an original spectrum and an approximation of it. The spectrum can be thought of as a continuous distribution. Since in Machine Learning we usually deal with observable data, we will consider dicrete
What is KullbackLeiblerSelector ? It is a feature selector based on the Kullback-Leibler divergence. A divergence is a measure of difference between two probabilistic distributions. In the case of machine learning, we can consider data distributions and calculate how different a certain feature column is compared to a target column. How
What is ICAFilter? It’s a filter that uses the Fast ICA algorithm. Unlike PCA that reduces the dimensions, Independent Component Analysis decomposes the mixed signals. After that it brings the filtered form of the pandas data frame as independent non-Gaussian signals. ICA will find these independent components, also called
What is ICAReducer? ICAReducer works as follows, it reduces the highly correlated features between them to one column. Is quite similar to PCAReducer, although it’s using the Fast ICA algorithm, which separates a mixed signal into additive subcomponents. Further, we will use ICAReducer to simplify a classification or regression
Feature selection is a really important task when it comes to complex data. One of the methods that could help us deal with it is the MultiSURF algorithm, that is a Relief-based Algorithm (RBA) — an individual evaluation filter method. The MultiSURF algorithm is using the Relief algorithm but is differentiated