Search Results for "multi-layer perceptron python" - Page 23
Sort By:
Showing 1057 open source projects for "multi-layer perceptron python"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Trumba is an All-in-one Calendar Management and Event Registration platformPublish, promote and track your events more affordably and effectively—all in one place.
-
1
TextRank
TextRank implementation for Python 3
TextRank is an implementation of the TextRank algorithm for extractive text summarization and keyword extraction, inspired by Google’s PageRank. -
2
DetectAndTrack
The implementation of an algorithm presented in the CVPR18 paper
DetectAndTrack is the reference implementation for the CVPR 2018 paper “Detect-and-Track: Efficient Pose Estimation in Videos,” focusing on human keypoint detection and tracking across video frames. The system combines per-frame pose detection with a tracking mechanism to maintain identities over time, enabling efficient multi-person pose estimation in video. Code and instructions are organized to replicate paper results and to serve as a starting point for researchers working on pose in... -
3
Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
...On common CNNs, it runs training 1.2~5x faster than the equivalent Keras code. Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not offer the data processing flexibility needed in research. Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. ... -
4
Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
-
5
Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. -
6
Deepvoice3_pytorch
PyTorch implementation of convolutional neural networks
An open source implementation of Deep Voice 3: Scaling Text-to-Speech with Convolutional Sequence Learning. -
7
WhatsappToDesktop
Esse é um pacote de compilado do Whatsapp Web versão 1.0.
Esse é um pacote de compilado do Whatsapp Web versão 1.0. Esse é um aplicativo multiplataforma de mensagens instantâneas e chamadas de voz para smartphones. Além de mensagens de texto, os usuários podem enviar vídeos, vídeos e documentos em formato PDF, além de fazer a livre conexão com o meio de uma conexão com internet ... -
8
Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual... -
9
Gin Config
Gin provides a lightweight configuration framework for Python
Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter... -
Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
-
10
PyEdit Editor
Configurable Editor in Python
PyEdit is a fully featured fast text editor written in Python. It can be used in any platform that has GTK. Because it is written in Python, it is easily configurable. Features code spell check and macro recording. Tested in Win/Lin/Mac --- Update: Using the editor full time V23 is mature enough for production --- Update: Had to downgrade to PyGTK 2.22.xx as 2,24,x had a double click message bug. (uploaded 22.2 to this project) --- Update: V33 is working as a champ. New... -
11
A project for a highly scalable protocol and framework and a collection of software tools for m2m (machine to machine communication) and IoT Internet of Things. The programs here works on Windows and Linux and are based around VSCP, The Very Simple Control Protocol. Repository is here: https://github.com/grodansparadis/vscp_software and here https://github.com/grodansparadis/vscp_firmware
-
12
RCPnet
A multi-tool for network pen-testing written in python.
A multi-tool for network pen-testing written in python. It contains effective ping functions, hostname traceroute, and cloudflare detection. This is a modification from the FoxNuke Project, which only intended to be a DOS tool for network pen testing. Contact me [main admin] at leyvarosnel@gmail.com -
13
Madara
Middleware for distributed applications
The purpose of the project is to develop a portable programming framework that facilitates distributed and multi-threaded programming for C++, Java, and Python. MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. ... -
14
DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
15
MultiBootUSB
Create multiboot live Linux on a USB disk
MultiBootUSB is a cross platform* software/utility to create multi boot live Linux on a removable USB disk. It is similar to UNetbootin but many distros can be installed, provided you have enough space on the disk. MultiBootUSB also provides an option to uninstall distro(s) at any time, if you wish. -
16
darc
Durham Adaptive-optics Real-time Controller
darc, the Durham Adaptive optics Real-time Controller. For documentation or darctalk client only, select "View all files". For the latest bleeding-edge version, please use: git clone git://git.code.sf.net/p/darc2/code darc (no password required) (this changed May 2013 due to a sourceforge update). If you use darc, please cite with: Basden, A and Myers, R, MNRAS Vol 242, page 1483, 2012 -
17
Universe Starter Agent
A starter agent that can solve a number of universe environments
The universe-starter-agent repository is an archived OpenAI codebase designed as a starter reinforcement-learning agent that can interact with and solve tasks in OpenAI’s Universe environment platform. Its purpose is to serve as a baseline or reference implementation so researchers or developers can see how to build agents that operate in real-time, visual environments (e.g., games, browser apps) via pixel observations and keyboard/mouse actions. Under the hood, this starter agent implements... -
18
DIGITS
Deep Learning GPU training system
The NVIDIA Deep Learning GPU Training System (DIGITS) puts the power of deep learning into the hands of engineers and data scientists. DIGITS can be used to rapidly train the highly accurate deep neural network (DNNs) for image classification, segmentation and object detection tasks. DIGITS simplifies common deep learning tasks such as managing data, designing and training neural networks on multi-GPU systems, monitoring performance in real-time with advanced visualizations, and selecting... -
19
D-Tailor
D-Tailor: automated analysis and design of DNA sequences
Recent advances in DNA cloning and synthesis technologies afford high throughput implementation of designed sequences into living cells. However, our ability to design sequences to interrogate multifactorial biological processes and further engineer biological functions is lagging behind. DNA-Tailor (D-Tailor) is a fully extendable software framework for biological sequence analysis and multi-objective sequence design. D-Tailor permits the seamless integration of an arbitrary number of... -
20
Database mapping layer for MongoDB on Python. Includes schema enforcement and some facilities for schema migration.
-
21
FAKE2DB
Create custom test databases that are populated with fake data
Generate fake but valid data filled databases for test purposes using most popular patterns(AFAIK). Current support is sqlite, mysql, postgresql, mongodb, redis, CouchDB. The installation through pypi retrieves 'fake-factory' as a main dependency. db argument takes 6 possible options, sqlite, mysql, postgresql, mongodb, redis, CouchDB. name argument is OPTIONAL. When it is absent fake2db will name db's randomly. host argument is OPTIONAL. Hostname to use for database connection. Not used for... -
22
multibootusb
Create multi boot live Linux on a USB disk...
Multi Boot USB / MultiBoot USB / MultiBootUSB is a software / installer which allows user to install multiple Live Linux Distros in to a single USB drive / Pendrive / Flash drive and able to boot from it. USB can be tested without reboot using inbuilt QEMU. -
23
txObject ATK is an OS independent C++ & Python object library. Built in the 90s, it provides a 5-layer framework: Object Library, IO / Timers, Threads, Inter-Process / Distributed Object Communication
-
24
Image classification models for Keras
Keras code and weights files for popular deep learning models
All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet'... -
25
PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested...
