Efficient Batched Reinforcement Learning in TensorFlow
A tool to graphically visualize SIMD code
Another OLAP database
A curated list of awesome SIMD frameworks, libraries and software
Plot in NumPy arrays directly, overlay NumPy plots straight over video real-time, plot in Jupyter without a single loop
Fast nonlinear FEA tailored for topology optimization
Accelerating convolution using numba, cupy and xnor in python
An Implementation of fuzzy clustering algorithms in Numpy
Vectroized String Helper Functions
Exercises, Descriptions, and Visualizations to build intuitions and confidence in working with PyTorch for accelerated Scientific Computing
Two-point connectivity statistics computation for hydrological patterns
While it is convenient to use advanced libraries for day-to-day modeling, it does not give insight into the details of what really happens underneath, when we run the codes. In this work, we implement a logistic regression model manually from scratch, without using any advanced library, to understand how it works.
A Hands-On NumPy Tutorial for Data Scientists
An ML+NLP solution for linking misspelled titles with the true titles
Collection of experiments to carve out the differences between two types of relational query processing engines: Vectorizing (interpretation based) engines and compiling engines.
Vectorized implementation of the image binarization algorithm of Su et al. (2010)
This repository shows code of programming tasks which I completed during Machine Learning course on Coursera.
Matrix multiplication speed comparison
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