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Python for Machine Learning course at TU Berlin. Introduction to Python and Python examples of machine learning algorithms with interactive Jupyter demos and math is applied.

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Python for Machine Learning Course at TU Berlin

Introduction to Python and Python examples of machine learning algorithms with interactive Jupyter demos and math is applied.

  1. Python Basics
  2. Inheritance, NumPy, Performance, Plotting
    • To determine if two arrays are broadcast compatible, check whether each of the aligned dimensions satisfy the either of the following conditions:
    • The aligned dimensions have the same size
    • One of the dimensions has a size of 1
  3. Analyzing a dataset, Randomness, Linear Algebra
  4. Simulation of Markov chains, Automatic differentiation, Numba, Cython
  5. Numerical instability, Pandas, Google colab

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Python for Machine Learning course at TU Berlin. Introduction to Python and Python examples of machine learning algorithms with interactive Jupyter demos and math is applied.

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