A concept I came up which ditches the idea of "layers" in a neural network.
Copy Dynet.py to your project.
Install matplotlib with pip install matplotlib to run the example in main.py.
Classic neural networks use layers as a way of organizing neurons. "Dynet" uses a single layers to process inputs and outputs where neurons can directly connect to outputs or pass through mutliple neurons and even connect to themselves
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms
CRAN Unofficial pytorch implementation of the paper "Context Reasoning Attention Network for Image Super-Resolution (ICCV 2021)" This code doesn't exa
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also includes simulation tools for generating plausible simulations of neural time series.
Educational python for Neural Networks, written in pure Python/NumPy.
📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.
Compare outputs of Wasserstein GANs between TensorFlow vs Pytorch This is our testing module for the implementation of improved WGAN in Pytorch Prereq
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks. Bayesian-Torch is designed to be flexible and seamless in extending a deterministic deep neural network architecture to corresponding Bayesian form by simply replacing the deterministic layers with Bayesian layers.
keytotext Idea is to build a model which will take keywords as inputs and generate sentences as outputs. Potential use case can include: Marketing Sea
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.
GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,
Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom
Discord Bot that leverages the idea of nested containers using podman, runs untrusted user input, executes Quantum Circuits, allows users to refer to the Qiskit Documentation, and provides the ability to search questions on the Quantum Computing StackExchange.
Card History At A Glance Stop having to press card browser and ctrl+i for every card and then WINCING to see it's history of reviews FEATURES Visualiz
No SeiQueLa ORM EM DESENVOLVIMENTO Uma ideia de ORM no estilo do Django para manipular entidades do Google Datastore. Montando seu modelo: from noseiq
Brief idea about our project is mentioned in project presentation file. You just have to run attendance.py file in your suitable IDE but we prefer jupyter lab.
GuessTheNumber GuessTheNumber is a simple game I made using Python. The main mechanic of the game is to guess the number that randomly generated from
NORETURN NORETURN is an esoteric programming language, based around the idea of not going back Concept Program coded in noreturn runs over one array,
Background This repository contains an implementation of Relaxed Linear Adversarial Concept Erasure (RLACE). Given a dataset X of dense representation
STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Fast k-NN graph construction for slow metrics
pyspark-anonymizer Python library which makes it possible to dynamically mask/anonymize data using JSON string or python dict rules in a PySpark envir
Diabetes Disease Prediction This is a machine Learning mode which tries to determine if a person has a diabetes or not. Data The dataset is in comma s
Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with
Movie-Success-Prediction A simple python program which predicts the success of a movie based on it's type, actor, actress and director. The program us
learn python in 100 days, a simple step could be follow from beginner to master of every aspect of python programming and project also include side project which you can use as demo project for your personal portfolio
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