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
Fast nonlinear FEA tailored for topology optimization
Vectroized String Helper Functions
An Implementation of fuzzy clustering algorithms in Numpy
Exercises, Descriptions, and Visualizations to build intuitions and confidence in working with PyTorch for accelerated Scientific Computing
Accelerating convolution using numba, cupy and xnor in python
An ML+NLP solution for linking misspelled titles with the true titles
Two-point connectivity statistics computation for hydrological patterns
Collection of experiments to carve out the differences between two types of relational query processing engines: Vectorizing (interpretation based) engines and compiling engines.
This repository shows code of programming tasks which I completed during Machine Learning course on Coursera.
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.
My finance tools in Python3
Matrix multiplication speed comparison
A Hands-On NumPy Tutorial for Data Scientists
In this repo I improve the performance of the LIBtft144 controller using numpy and vector operations, and use it to show in real-time the image stream from my raspberry-pi camera on a SPI 144 display
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