Plain python implementations of basic machine learning algorithms
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Updated
May 21, 2024 - Jupyter Notebook
Plain python implementations of basic machine learning algorithms
Python implementations of selected Princeton Java Algorithms and Clients by Robert Sedgewick and Kevin Wayne
Some python implementations from the book, "Reinforcement Learning: An Introduction" by Andrew Barto and Richard S. Sutton.
easy graph implementation
k-means / k-means++ / elbow-method
Fourier transform properties
Dynamic Mode Decomposition (DMD)
Algebraic Reconstruction Technique (ART)
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
💻 Data Structures and Algorithms in Python
C++ and Python implementations of converting degrees to quaternion
Unique python implementations
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
These are the Python implementations of FIFO, LRU and OPT page replacement algorithms
Python implementations of Deep Learning models and algorithms with a minimum use of external library.
Basic ML algorithms written from scratch in python using numpy.
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