TensorFlow and Deep Learning Tutorials
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Updated
Feb 26, 2018
TensorFlow and Deep Learning Tutorials
Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).
Predicting Amsterdam house / real estate prices using Ordinary Least Squares-, XGBoost-, KNN-, Lasso-, Ridge-, Polynomial-, Random Forest-, and Neural Network MLP Regression (via scikit-learn)
Official implementation of MLP Singer: Towards Rapid Parallel Korean Singing Voice Synthesis (IEEE MLSP 2021)
An example project using a feed-forward neural network for text sentiment classification trained with 25,000 movie reviews from the IMDB website.
[ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
Stock price trend prediction with news sentiment analysis using deep learning
Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
我的笔记和Demo,包含分类,检测、分割、知识蒸馏。
Neuron class provides LNU, QNU, RBF, MLP, MLP-ELM neurons
This repository is MLP implementation of classifier on MNIST dataset with PyTorch
C++ demo of deep neural networks (MLP, CNN)
Recognize Digits using Deep Neural Networks in Google Chrome live!
Deep Convolutional Neural Networks for Raman Spectrum Recognition. (RRUFF dataset)
Detecting Fraudulent Blockchain Accounts on Ethereum with Supervised Machine Learning
Value or Momentum? Comparing Random Forests, Support Vector Machines, and Multi-layer Perceptrons for Financial Time Series Prediction & Tactical Asset Allocation
Pixel based classification of satellite imagery - feature generation using Orfeo Toolbox, feature selection using Learning Vector Quantization, CLassification using Decision Tree, Neural Networks, Random Forests, KNN and Naive Bayes Classifier
Minerva project includes the minerva package that aids in the fitting and testing of neural network models. Includes pre and post-processing of land cover data. Designed for use with torchgeo datasets.
EE7207 Neural & Fuzzy Systems
Image Classification on CIFAR-10 Dataset using Multi Layer Perceptrons in Python from Scratch.
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