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The Engauge Digitizer tool accepts image files (like PNG, JPEG and TIFF) containing graphs, and recovers the data points from those graphs. The resulting data points are usually used as input to other software applications. Conceptually, Engauge Digitizer is the opposite of a graphing tool that converts data points to graphs.
PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective.
Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. The details of these algorithms are described in the PySR paper.
Symbolic regression works best on low-dimensional datasets, but one can also extend these approaches to higher-dimensional spaces by using "Symbolic Distillation" of Neural Networks, as explained in 2006.11287, where we apply it to N-body problems. Here, one essentially uses symbolic regression to convert a neural net to an analytic equation. Thus, these tools simultaneously present an explicit and powerful way to interpret deep neural networks.
CFD Python Online Course
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Applied Machine Learning in Python
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Online educational materials for self-learners of CFD using IPython Notebooks: the CFD Python Class
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https://wiki.python.org/moin/BeginnersGuideChinese
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