AI Today Podcast

The Perceptron was the first artificial neuron. The theory of the perceptron was first published in 1943 by McCulloch & Pitts, and then developed in 1958 by Rosenblatt. So yes, this was developed in the early days of AI. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Perceptron and explain how the term relates to AI and why it’s important to know about it.Continue reading AI Today Podcast: AI Glossary Series – Perceptron at Cognilytica.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bias, Weight, Activation Function, Convergence, and ReLU and explain how they relate to AI and why it’s important to know about them.Show Notes:FREE Intro to CPMAI mini courseCPMAI Training and CertificationAI GlossaryAI Glossary Series – Machine Learning, Algorithm, ModelGlossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement LearningGlossary Series: Dimension, Curse of Dimensionality, Dimensionality ReductionGlossary Series: Feature, Feature EngineeringGlossary Series: (Artificial) Neural Networks, Node (Neuron), LayerContinue reading AI Today Podcast: AI Glossary Series – Bias, Weight, Activation Function, Convergence, and ReLU at Cognilytica.

If we can replicate neurons and how they are connected, can we replicate the behavior of our brains? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms (Artificial) Neural Networks, Node, and layer, and explain how they relate to AI and why it’s important to know about them.Continue reading AI Today Podcast: AI Glossary Series – (Artificial) Neural Networks, Node (Neuron), Layer at Cognilytica.

For a number of reasons, it can be important to reduce the number of variables or identified features in input training data so as to make training machine learning models faster and more accurate. But what are the techniques for doing this? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Feature Reduction, Principal Component Analysis (PCA), and t-SNE, explain how they relate to AI and why it’s important to know about them.Continue reading AI Today Podcast: AI Glossary Series – Feature Reduction, Principal Component Analysis (PCA), and t-SNE at Cognilytica.

Learn about the importance of features and feature engineering in machine learning, how they enhance AI models, and their impact on project success. Dive into the CPMAI methodology and free certification course offered to improve AI project outcomes.

Regression is a statistical and mathematical technique to find the relationship between two or more variables. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Regression and Linear Regression and explain how they relate to AI and why it’s important to know about them.Show Notes:FREE Intro to CPMAI mini courseCPMAI Training and CertificationAI GlossaryAI Glossary Series – Machine Learning, Algorithm, ModelGlossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement LearningGlossary Series: Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision BoundaryGlossary Series: Clustering, Cluster Analysis, K-Means, Gaussian Mixture ModelContinue reading AI Today Podcast: AI Glossary Series – Regression and Linear Regression at Cognilytica.

The idea of grouping similar types of data together is the main idea behind clustering. Clustering supports the goals of Unsupervised Learning which is finding patterns in data without requiring labeled datasets. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Clustering, Cluster Analysis, K-Means, and Gaussian Mixture Model, and explain how they relate to AI and why it’s important to know about them.Continue reading AI Today Podcast: AI Glossary Series- Clustering, Cluster Analysis, K-Means, Gaussian Mixture Model at Cognilytica.

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define DeepBlue, including what it is and why it’s notable for AI.Show Notes:FREE Intro to CPMAI mini courseCPMAI Training and CertificationAI GlossaryAI Glossary Series – Symbolic Systems & Expert SystemsAI Glossary Series: Cognitive TechnologyContinue reading AI Today Podcast: AI Glossary Series – Deep Blue at Cognilytica.

Before this latest wave of AI where neural nets became the hottest algorithm of choice, an approach to machine learning that uses logic and constructs similar to the way that humans reason through problems called Symbolic Systems were actually the system of choice. Popularized in the late 1980s and early 1990s expert systems became the AI system of choice for organizations investing in cognitive technology.Continue reading AI Today Podcast: AI Glossary Series: Symbolic Systems & Expert Systems at Cognilytica.

Sometimes for reasons such as improving performance or robustness it makes sense to create multiple decision trees and average the results to solve problems related to overfitting. Or, it makes sense to boost certain decision trees. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Random Forest and Boosted Trees, and explain how they relate to AI and why it’s important to know about them.Continue reading AI Today Podcast: AI Glossary Series – Random Forest and Boosted Trees at Cognilytica.