Introduction to deep learning

Machine learning training


Python syntax
Solid knowledge of basic machine learning ideas
(validation methods, gradient descent algorithm, preventing overfitting)
machine learning experience

Skills your team will gain

Knowledge of selected deep learning concepts and algorithms.

The ability to create deep learning algorithms in PyTorch or Keras.

The ability to create pipelines for solving real-life problems.

Tools and metrics for evaluating deep learning models.


2 days


Part 1

Deep learning algorithms with PyTorch or Keras

  • The programming environment: PyTorch or Keras
  • Layer types in detail: dense, convolutional, max-pooling layers
  • Case study: fully connected network, convolutional neural network

Part 2

Different architectures for different needs

  • Transfer learning
  • Highlight of advanced deep learning architectures
  • U-Net implementation

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