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Practicum AI: Deep Learning Foundations

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Module 1: Neural Network Basics Objectives

By the end of this module, you will be able to:

  1. Define a neural network.
  2. Describe how a neural network works.
  3. Discuss deep networks.
  4. Discuss what can be done with neural networks.
  5. Use a deep learning pre-trained model to classify an image.
  6. Discuss Python AI Frameworks.

Module 2: Neural Network Advanced Objectives

By the end of this module, you will be able to:

  1. Describe the basis of a neural network (neuron).
  2. Identify and describe an artificial neuron (perceptron).
  3. Discuss bias and weights.
  4. Describe and identify activation functions.
  5. Describe and simulate image processing in a small neural network.
  6. Implement and train a perceptron using TensorFlow.

Module 3 Optimization Algorithms and Hyperparameter Tuning Objectives

By the end of this module, you will be able to:

  1. Describe the purpose and process of gradient descent.
  2. Discuss the error loss function.
  3. Describe optimizers.
  4. Experiment with hyperparameter tuning.

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