AI Today Podcast

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms CPU, GPU, TPU, and Federated Learning, explain how these terms relate to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Continue reading AI Today Podcast: AI Glossary Series – CPU, GPU, TPU, and...

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Tokenization and Vectorization, explain how these terms relates to AI and why it’s important to know about them. Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest t...

In order for machine learning systems to work they need to be trained on data. But as the old saying goes “garbage in is garbage out” so you need to make sure you have a dataset of prepared data that is cleaned so you can incrementally train a machine learning model to perform a particular task. Continue reading AI Today Podcast: AI Glossary Series – Training Data, Epoch, Batch, Learning Curve at...

Backpropagation was one of the innovations by Geoff Hinton that made deep learning networks a practical reality. But have you ever heard of that term before and know what it is at a high level? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Backpropagation, Learning Rate, and Optimizer, explain how these terms relates to AI and why it’s important to...

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Loss Function, Cost Function and Gradient Descent, explain how these terms relates to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Artificial Intelligence Glossary Series: Artificial General Intell...

Deep Learning is powering this current wave of AI interest. But do you really know what Deep Learning is? In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms hidden layer and deep learning, explain how these terms relates to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series- Hidden Layer and Deep Learning...

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...

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 course CPMAI Training and Certification AI Glossary AI Glossary Series – Machine Learning, Algorithm, Model Glossary Series: Machine...

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 Net...

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-S...

For time-consuming parts of the machine learning workflow people often look for tricks and techniques to help speed up the process. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms feature and feature engineering, explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Feature an...

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 course CPMAI Training and Certification AI Glo...

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 rel...

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 course CPMAI Training and Certification AI Glossary AI Glossary Series – Symbolic Systems & Expert Systems AI Glossary Series: Cognitive Technology Continue reading AI Today Podcast: AI Glossary Series – Deep Blue...

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 t...

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...

Sometimes for reasons such as improving performance or robustness it makes sense to combine the results of multiple different models trained on the same data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Ensemble Models, and explain how it relates to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series...

There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Decisio...

There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Support Vector Machine & Kernel Method, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series – Support...

There are many algorithms that can be used for classification and it’s important to at least know them at a high level. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms K-Nearest Neighbor and Lazy Learning, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Glossary Series: K-Nearest Neig...

Probabilities play a big part in AI and machine learning. After all, AI systems are Probabilistic systems that must learn what to do. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Bayes’ Theorem, Bayesian Classifier, Naive Bayes, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI Gloss...

Determining which categories or “classes” data belongs to in the core aspect of classification. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary, and explain how they relate to AI and why it’s important to know about them. Continue reading AI Today Podcast: AI...

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer have a discussion with Bill Raymond who is the host of the Agile In Action podcast. We discuss why project managers should pay attention to AI, how the areas of Agile and AI are intersecting, and how artificial intelligence fits within the project management space both from running AI projects to also how AI will enhanc...

When it comes to building ML models, you want to make a model simple enough so that it can handle a wide range of real-world data on the one hand, but not too simple that it overgeneralizes or underfits the available data. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Overfitting, Underfitting, Bias, Variance, and Bias/Variance Tradeoff, and explai...

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Dimension, Curse of Dimensionality, Dimensionality Reduction, and explain how they relate to AI and why it’s important to know about them. Show Notes: FREE Intro to CPMAI mini course CPMAI Training and Certification AI Glossary Glossary Series: Artificial Intelligence AI Glossary Series – Machine Learni...