Basic ML algorithms written from scratch in python using numpy.
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Updated
Jan 2, 2016 - Python
Basic ML algorithms written from scratch in python using numpy.
Python implementations of Deep Learning models and algorithms with a minimum use of external library.
These are the Python implementations of FIFO, LRU and OPT page replacement algorithms
A collection of python implementations using SWIG, Instant, F2PY... Optimization like Least Squares Levenberg-Marquardt. Boundary Value problem solvers. Integration Simpson/Trapezoidal. Interpolation like Cubic spline. Tridiagonal/pentadiagonal system of equations solver. Linear algebra like Matrix inversion (Gauss-Jordan) and much more
Unique python implementations
C++ and Python implementations of converting degrees to quaternion
💻 Data Structures and Algorithms in Python
python implementations of the Flajolet-Martin, LogLog, SuperLogLog, and HyperLogLog cardinality estimation algorithms, specifically used to estimate the cardinality of unique traffic violations in NYC in the 2019 fiscal year
Algebraic Reconstruction Technique (ART)
Dynamic Mode Decomposition (DMD)
Fourier transform properties
k-means / k-means++ / elbow-method
easy graph implementation
Some python implementations from the book, "Reinforcement Learning: An Introduction" by Andrew Barto and Richard S. Sutton.
Python implementations of selected Princeton Java Algorithms and Clients by Robert Sedgewick and Kevin Wayne
Plain python implementations of basic machine learning algorithms
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