In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Science Notebooks, Jupyter, Colab, explain how these terms relate to AI and why it's important to k

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Automated Machine Learning (AutoML), explain how this term relate to AI and why it's important to know ab

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning Tools: Keras, PyTorch, Scikit Learn, TensorFlow, Apache Spark, Kaggle, explain how thes

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Machine Learning Development Languages: Python, R, Julia, Scala, explain how these terms relate to AI an

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms DevOps, Machine Learning Operations (ML Ops), explain how these terms relate to AI and why it's importan

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Data Drift, Model Drift, Model Retraining, explain how these terms relate to AI and why it's important t

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Cloud ML, On-Premise, Edge Device, Machine Learning -as-a-Service (MLaaS), explain how these terms relat

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Batch Prediction, Microservice, Real-time Prediction, Stream Learning, Cold-Path Analytics, and Hot-Path

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Operationalization, explain how this term relates to AI and why it's important to know about them. Sho

In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Digital Transformation, Return on Investment (ROI), and Key Performance Indicator (KPI), explain how the