Advanced ML Methods: Neural Networks and Deep Learning

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Advanced ML Methods: Neural Networks and Deep Learning is starter course for more complex machine learning with neural networks, using Keras on top of TensorFlow.


This course is suitable for: Tech Analysts, S&T Analysts (optionally).

Learning Outcomes

Describe the core concepts in neural networks:

  • Neurons and perceptions
  • Layers
  • Feedback functions
  • Deep learning

Enumerate some of the key NNs that can be used in analytics, and their typical applications:

  • LTSTM (Long Term Short Term Memory)
  • CNN (Convolutional Neural Networks

Make an informed choice on which NN architecture to use for a given use case through a hands-on programming case study

Course Content

• Neural network types: CNN, LSTM
• What neural networks can do: automatic feature selection
• Batches and epochs
• Hyperparameter tuning
• How to avoid under-and overfitting
• Workshop: implement a logistic regression using Keras and TF. How does it perform relative to other approaches?


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