AI Today Podcast

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 Cognilytica.

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 know about them.

Continue reading AI Today Podcast: AI Glossary Series – Backpropagation, Learning Rate, and Optimizer at Cognilytica.

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 Intelligence (AGI), Strong AI, Weak AI, Narrow AI
• Glossary Series: Heuristic & Brute-force Search
• AI Glossary Series – Machine Learning, Algorithm, Model
• Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer
• Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU
• Glossary Series: Perceptron
• Glossary Series: Hidden Layer, Deep Learning

Continue reading AI Today Podcast: AI Glossary Series – Loss Function, Cost Function and Gradient Descent at Cognilytica.

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 at Cognilytica.

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 course
• CPMAI Training and Certification
• AI Glossary
• AI Glossary Series – Machine Learning, Algorithm, Model
• Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning
• Glossary Series: Dimension, Curse of Dimensionality, Dimensionality Reduction
• Glossary Series: Feature, Feature Engineering
• Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer

Continue 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.

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 and Feature Engineering at Cognilytica.

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 Glossary
• AI Glossary Series – Machine Learning, Algorithm, Model
• Glossary Series: Machine Learning Approaches: Supervised Learning, Unsupervised Learning, Reinforcement Learning
• Glossary Series: Classification & Classifier, Binary Classifier, Multiclass Classifier, Decision Boundary
• Glossary Series: Clustering, Cluster Analysis, K-Means, Gaussian Mixture Model

Continue reading AI Today Podcast: AI Glossary Series – Regression and Linear Regression at Cognilytica.