Linear regression

Statistics and Probability > Exploring bivariate numerical data

Logistic regression

Neural Networks and Deep Learning

Neural Networks and Deep Learning

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  • Very basic programming skills (i.e. ability to work with dictionaries and for loops)
  • basic machine learning (how do we represent a dataset as a matrix, etc.).
  • basic linear algebra (matrix multiplications, vector operations etc.).

Python has a useful library “Numpy” that makes math operations very easy.
deep learning frameworks:

  • Tensorflow
  • Keras
  • PaddlePaddle,
  • CNTK
  • Caffe, …

Geoffrey Hinton interview
27:42 unsupervised learning: how to do it?


Science in 60 Seconds: Cyclotron!
University of Alabama at Birmingham
Published on Feb 26, 2014

IBA radiopharmaceutical production solutions
ibagroup. Feb 18, 2014
Would you like to know how a PET center works?