Tutorial code on how to build your own Deep Learning System in 2k Lines
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Updated
Oct 4, 2018 - C++
Tutorial code on how to build your own Deep Learning System in 2k Lines
Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communication.
A collection of all projects pertaining to different layers in the SDC software stack
Interactive Notation for Computational Graphs
AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.
Strongly-typed, dependency based application framework for code/data separation with dependency injection and data passing.
C++ implementation of neural networks library with Keras-like API. Contains majority of commonly used layers, losses and optimizers. Supports sequential and multi-input-output (flow) models. Supports single CPU, Multi-CPU and GPU tensor operations (using cuDNN and cuBLAS).
ICDSS Machine Learning Workshop Series: Neural Networks
Model-based Policy Gradients
A computational graph for time-series processing.
Code for "Can We Scale Transformers to Predict Parameters of Diverse ImageNet Models?" [ICML 2023]
Automatic differentiation in python
A graph-oriented algorithmic engine
Network-wide estimation of traffic flow and travel time with data-driven macroscopic models
Yet another tensor automatic differentiation framework
Library to manipulate tensors on the GPU.
A deep learning library for golang
An aggregation of my experiments in Neural Networks and Deep Learning using TensorFlow.
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