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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:
- FREE Intro to CPMAI mini course
- CPMAI Training and Certification
- 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
