Efficient Batched Reinforcement Learning in TensorFlow
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Updated
Jan 11, 2019 - Python
Efficient Batched Reinforcement Learning in TensorFlow
The amazing multi-processor 8-bit microcomputer, featuring Z80, 6502 and AVR processors. Built with CPLDs, CERBERUS 2100™ is fully programmable even with respect to its hardware, at the individual gate and flip-flop level.
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Mpcurses is an abstraction of the Python curses and multiprocessing libraries providing function execution and runtime visualization capabilities.
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Examples on multi-processing and multi-threading in Python.
Course repository for parallel programming. Includes the usage of concepts like multi-processing, threads, mutex, shared memory, locks, etc.
a hybrid CPU-GPU combined multi-processing approach for optimized performance in AES128 algorithm. The encryption key is derived using the HKDF (HMAC-based Key Derivation Function) combined with the scrypt algorithm for added security.
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