Treffer: Probability for machine learning: discover how to harness uncertainty with Python

1 online resource (1 PDF file (xvii, 301 pages)) + 1 folder of code examples in text format). System requirements: Adobe Reader and text file reader such as Notepad. ; Probability is foundational to machine learning and required background for machine learning practitioners. Probability is a prerequisite in most courses and books on applied machine learning. Probability methods are used at each step in an applied machine learning project. Probabilistic frameworks underlie the training of many machine learning algorithms. Data distributions and statistics don't make sense without probability. Fitting models on a training dataset does not make sense without probability. Interpreting the performance of a stochastic learning algorithm does not make sense without probability. A machine learning practitioner cannot be effective without an understanding and appreciation of the basic concepts and methods from the field of probability.