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Most of our graduates found jobs in machine learning

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OR contact us 0723935447

Participants

The course is tailored for individuals with no prior knowledge of machine learning, yet have a strong scientific academic background.
In order to participate you must have a Bachelor’s degree or higher in mathematics or a scientific field.

Linear algebra knowledge especially is a prerequisite for the course.

February 2018

Unsupervised Learning

  • Clustering
  • K-Means
  • Dimensionality reduction
  • PCA

Supervised learning

  • Perceptron
  • Linear regression
  • SVM and kernel methods
  • Decision trees
  • Bayesian methods
  • Neural networks

Deep Learning

  • Neural network learning: Back-Propagation
  • CNN architectures
  • Generative Adversarial Networks (GANs)
  • Recurrent Neural networks (RNNs)
  • Advanced RNN: LSTM, GRU, nLSTM
  • Deep reinforcement learning

Theory

  • Formalization of learning
  • VC dimension
  • PAC theory
  • Bias – Variance tradeoff

We also offer placement services for our graduates, and outsourcing services. If you want to hire good and well trained data scientists – contact us: info@deep-learning-academy.com

Apply Now!
We look forward to having you with us!
Phone: 0723935447
Email: 
info@deep-learning-academy.com

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