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gradient-descent
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Fast and Easy Infinite Neural Networks in Python
kernel
neural-networks
gradient-descent
bayesian-inference
gaussian-processes
bayesian-networks
deep-networks
gradient-flow
jax
infinite-networks
training-dynamics
neural-tangents
kernel-computation
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May 10, 2020 - Jupyter Notebook
A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN
machine-learning
visual-studio
ai
csharp
neural-network
cuda
cnn
supervised-learning
gpu-acceleration
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convolutional-neural-networks
gradient-descent
net-framework
backpropagation-algorithm
classification-algorithims
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May 1, 2020 - C#
This repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
data-science
machine-learning
tutorial
deep-learning
sentiment-analysis
neural-network
numpy
scikit-learn
keras
semicolon
lstm
rnn
matplotlib
convolutional-neural-networks
perceptron
gradient-descent
cnn-keras
scikit
pandas-tutorial
count-vectorizer
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Jan 16, 2018 - Jupyter Notebook
The simplest form of an artificial neural network explained and demonstrated.
golang
machine-learning
tutorial
artificial-intelligence
artificial-neural-networks
gradient-descent
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Jan 4, 2020 - Go
OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions
newton
cpp
optimization
openmp
cpp11
evolutionary-algorithms
armadillo
gradient-descent
optim
differential-evolution
optimization-algorithms
particle-swarm-optimization
bfgs
lbfgs
openmp-parallelization
numerical-optimization-methods
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Apr 25, 2020 - C++
Implementing Multiple Layer Neural Network from Scratch
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Apr 14, 2016 - Python
Six snippets of code that made deep learning what it is today.
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Oct 10, 2019 - Jupyter Notebook
A PyTorch implementation of Learning to learn by gradient descent by gradient descent
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Aug 27, 2018 - Python
Heterogeneous automatic differentiation ("backpropagation") in Haskell
deep-learning
neural-network
graph
automatic-differentiation
gradient-descent
backpropagation
backprop
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Nov 5, 2019 - Haskell
Starter code of Prof. Andrew Ng's machine learning MOOC in R statistical language
machine-learning
neural-network
clustering
svm
linear-regression
pca
classification
recommender-system
regularization
gradient-descent
k-means
anomalydetection
principal-component-analysis
learning-curve
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Jul 12, 2018 - R
Gradient based hyperparameter optimization & meta-learning package for TensorFlow
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Mar 24, 2020 - Jupyter Notebook
MATLAB library for non-negative matrix factorization (NMF): Version 1.8.0
matlab
machine-learning-algorithms
bigdata
matrix-factorization
constrained-optimization
data-analysis
robust-optimization
gradient-descent
matlab-toolbox
clustering-algorithm
optimization-algorithms
nmf
online-learning
stochastic-optimizers
stochastic-gradient-descent
nonnegativity-constraints
orthogonal
probabilistic-matrix-factorization
nonnegative-matrix-factorization
sparse-representations
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Jun 27, 2019 - MATLAB
A curated list of mathematics documents ,Concepts, Study Materials , Algorithms and Codes available across the internet for machine learning and deep learning
machine-learning
algorithm
deep-learning
static-analysis
linear-algebra
probability
mathematics
gradient-descent
approximation-algorithms
machine-learning-mathematics
deep-learning-mathematics
advanced-probability
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Aug 11, 2017
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
python
machine-learning
clustering
linear-regression
regression
neural-networks
supervised-learning
pca
classification
dimensionality-reduction
logistic-regression
recommender-system
gradient-descent
support-vector-machines
backpropagation
anomaly-detection
unsupervised-machine-learning
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Jan 10, 2019 - Jupyter Notebook
Projects from the Deep Learning Specialization from deeplearning.ai provided by Coursera
deep-neural-networks
ai
deep-learning
neural-network
tensorflow
keras
jupyter-notebook
rnn
matplotlib
gradient-descent
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backpropagation
keras-neural-networks
poetry-generator
numpy-tutorial
lstm-neural-networks
cnn-for-visual-recognition
deeplearning-ai
cnn-classification
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Sep 8, 2018 - Jupyter Notebook
Multiple Regression Package for PHP
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Sep 22, 2018 - PHP
Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!
monte-carlo
machine-learning-algorithms
gradient-descent
mcmc
evolution-strategies
stock-market-monte-carlo
deep-learning-scratch
feed-forward-scratch
rnn-scratch
cnn-scratch
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Jun 23, 2019 - Jupyter Notebook
Differentiable RayTracing in Julia
machine-learning
optimization
julia
ray-tracer
raytracer
gradient-descent
gpu-support
mesh-rendering
differentiable-programming
inverse-rendering
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May 25, 2020 - Julia
Some experiments about Machine Learning
machine-learning
classification
gradient-descent
frequent-itemset-mining
regression-models
chinese-word-segmentation
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Dec 10, 2018 - Python
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Nov 14, 2019 - Python
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Dec 28, 2017 - JavaScript
simple machine learning demo
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Dec 5, 2017 - JavaScript
Final Project of the Udacity AI Programming with Python Nanodegree
python
udacity
ai
numpy
python3
pytorch
neural-networks
image-classification
image-recognition
matplotlib
deeplearning
gradient-descent
backpropagation-learning-algorithm
udacity-nanodegree
perceptron-learning-algorithm
pytorch-implmention
udacity-ai-nanodegree
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Aug 16, 2018 - Jupyter Notebook
My workshop on machine learning using python language to implement different algorithms
python
machine-learning
workshop
deep-learning
numpy
scikit-learn
keras
dropout
batch-normalization
neural-networks
matplotlib
convolutional-neural-networks
gradient-descent
backpropagation
optimization-algorithms
softmax
machine-learning-workshop
linear-classification
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Jan 24, 2020 - Jupyter Notebook
alexanderchernyakovgithub
commented
Sep 29, 2017
I noticed in the vignette it alludes to being able to stream data to sgd via bigmemory but I can't seem to find any examples of how to do this. Could you please provide some in the docs?
An Image classifier to identify whether the given image is Batman or Superman using a CNN with high accuracy. (From getting images from google to saving our trained model for reuse.)
python
tensorflow
dnn
neural-networks
image-classification
image-classifier
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deeplearning
convolutional-neural-networks
gradient-descent
batman
cnn-model
tensorflow-models
cnn-architecture
cnn-classifier
cnn-tensorflow
bvs
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Dec 8, 2019 - Python
Artificial intelligence/machine learning course at UCF in Spring 2020 (Fall 2019 and Spring 2019)
machine-learning
deep-learning
linear-regression
feature-extraction
logistic-regression
convolutional-neural-networks
gradient-descent
pretrained-models
data-augmentation
backpropagation-algorithm
keras-tensorflow
fine-tuning
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Apr 20, 2020 - Jupyter Notebook
Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.
python
machine-learning
text-mining
neural-network
word2vec
word-embeddings
web-scraping
lstm
expectation-maximization
gradient-descent
text-processing
lda
text-prediction
scraping-websites
latent-dirichlet-allocation
skipgram
gibbs-sampling
long-short-term-memory-models
word-embedding
textual-analysis
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Sep 21, 2017 - Jupyter Notebook
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In operations_broadcast_test.go there are some tests that are not yet filled in. The point is to test that broadcasting works for different shapes. The semantics of broadcast probably isn't clear, so please do send me a message for anything.
This is a good first issue for anyone looking to get interested