Keras Training Courses in Luxembourg

Keras Training Courses

Online or onsite, instructor-led live Keras training courses demonstrate through interactive hands-on practice how to use Keras for fast experimentation with deep neural networks.

Keras training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Keras trainings in Luxembourg can be carried out locally on customer premises or in NobleProg corporate training centers.

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Keras Course Outlines in Luxembourg

Course Name
Duration
Overview
Course Name
Duration
Overview
21 hours
This instructor-led, live training in Luxembourg (online or onsite) is aimed at technical persons who wish to apply deep learning model to image recognition applications. By the end of this training, participants will be able to:
  • Install and configure Keras.
  • Quickly prototype deep learning models.
  • Implement a convolutional network.
  • Implement a recurrent network.
  • Execute a deep learning model on both a CPU and GPU.
21 hours
This instructor-led, live training in Luxembourg (online or onsite) is aimed at developers who wish to build a self-driving car using deep learning techniques. By the end of this training, participants will be able to:
  • Use Keras to build and train a convolutional neural network.
  • Use computer vision techniques to identify lanes in an autonomos driving project.
  • Train a deep learning model to differentiate traffic signs.
  • Simulate a fully autonomous car.
14 hours
This instructor-led, live training in Luxembourg (online or onsite) is aimed at software engineers who wish to develop advanced deep learning neural-networks and model using Keras and Python. By the end of this training, participants will be able to:
  • Apply deep learning with supervised or unsupervised learning methods.
  • Develop, train, and implement concurrent neural networks and recurrent neural networks.
  • Use Keras and Python to build deep learning models to solve problems involving images, text, sound, and more.

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