AI Today Podcast: AI Glossary Series – Automated Machine Learning (AutoML)

Many organizations want to do AI, but the technical skills needed can present a challenge. Not all organizations have data scientists on hand. Yet, many organizations still want to benefits of AI. In recent years there have been tools and platforms created to help automate many of the aspects of building and developing ML models that previously required very specialized skills and talent. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Automated Machine Learning (AutoML).

Tools and platforms used to help automate many aspects of building and developing machine learning models as well as underlying data is AutoML in a nutshell. These tools can be used by experienced practitioners or so called “citizen data scientists”.

Show Notes:

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AI Glossary

AI Glossary Series - DevOps, Machine Learning Operations (ML Ops)

AI Glossary Series - Model Tuning and Hyperparameter

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

Glossary Series: Loss Function, Cost Function & Gradient Descent

Glossary Series: Backpropagation, Learning Rate, Optimizer

Glossary Series: Feed-Forward Neural Network

AI Glossary Series - Machine Learning, Algorithm, Model

AI Glossary Series - Model Tuning and Hyperparameter