Search Results for "learning system" - Page 6
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Showing 192 open source projects for "learning system"
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TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
...Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the theory of transfer learning and show how to apply it in useful projects. The development is on progress! The API will be updated soon, the more talented and light-weight API will be available in this repo! Detailed API documentation and sample jupyter notebooks that explain basic usages of API will be added! -
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PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
PyTorch-BigGraph (PBG) is a system for learning embeddings on massive graphs—think billions of nodes and edges—using partitioning and distributed training to keep memory and compute tractable. It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. -
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models,... -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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Active Learning
Framework and examples for active learning with machine learning model
Active Learning is a Python-based research framework developed by Google for experimenting with and benchmarking various active learning algorithms. It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. ... -
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CakeChat
CakeChat: Emotional Generative Dialog System
CakeChat is a backend for chatbots that are able to express emotions via conversations. The code is flexible and allows to condition model's responses by an arbitrary categorical variable. For example, you can train your own persona-based neural conversational model or create an emotional chatting machine. Hierarchical Recurrent Encoder-Decoder (HRED) architecture for handling deep dialog context. Multilayer RNN with GRU cells. The first layer of the utterance-level encoder is always... -
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Scalable Distributed Deep-RL
A TensorFlow implementation of Scalable Distributed Deep-RL
Scalable Agent is the open implementation of IMPALA (Importance Weighted Actor-Learner Architectures), a highly scalable distributed reinforcement learning framework developed by Google DeepMind. IMPALA introduced a new paradigm for efficiently training agents across large-scale environments by decoupling acting and learning processes. In this architecture, multiple actor processes interact with their environments in parallel to collect trajectories, which are then asynchronously sent to a centralized learner for policy updates. ... -
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CMD Plot Tool
Calculates and plots Colour Magnitude Diagrams from Astronomical data
...It can handle multiple file formats (plain text, DAOPHOT .mag files, ACS Survey of Galactic Globular Clusters .zpt files) to generate professional and customised plots, without the usual steep learning curve. Development using Python, OOP and a formal software development lifecycle model (Agile) allowed for the creation of an application that can be deployed on multiple systems. It works “out of the box” and does not require any installation of development environments, additional libraries or resetting of system paths. The tool is available as a single application/executable file, with the source code, on Sourceforge. ... -
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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 prediction). ... -
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CRP - Chemical Reaction Prediction
Predicting Organic Reactions using Neural Networks.
The intend is to solve the forward-reaction prediction problem, where the reactants are known and the interest is in generating the reaction products using Deep learning. This Graphical User Interface takes simplified molecular-input line-entry system (SMILES) as an input and generates the product SMILE & molecule. Beam search is used in Version 2, to generate top 5 predictions. Maximum input length for the model is 15 (excluding spaces). -
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virgo
32 bit VIRGO Linux Kernel
Linux kernel fork-off with cloud and machine learning features -
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AngelReader
An E-book, Audio-book, & Library Loader in One Application
...It can also load [2] Audio-books with the basic functions of play, stop, pause, and resume with the same minimalist economy that doesn't hog computer resources. When used in integration with the AngelReader Library Selector, it can function as a mini library management system for books in electronic formats. It's in fact three apps integrated into one intuitively portable, cross platform, robust software. The app can be useful for either classroom or office environment; for personal or commercial use; for general learning or access to practical information. -
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Face Recognition
World's simplest facial recognition api for Python & the command line
Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a... -
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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 the best performing model from the results browser for deployment. ... -
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The Deep Review
A collaboratively written review paper on deep learning, genomics, etc
...Like the initial release, we are planning for an open and collaborative effort. New contributors are welcome and will be listed as version 2.0 authors. Manubot is a system for writing scholarly manuscripts via GitHub. Manubot automates citations and references, versions manuscripts using git, and enables collaborative writing via GitHub. -
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DC-TTS
TensorFlow Implementation of DC-TTS: yet another text-to-speech model
DC-TTS is a TensorFlow implementation of the DC-TTS architecture, a fully convolutional text-to-speech system designed to be efficiently trainable while producing natural speech. It follows the “Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention” paper, but the author adapts and extends the design to make it practical for real experiments. The model is split into two networks: Text2Mel, which maps text to mel-spectrograms, and SSRN... -
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Intel neon
Intel® Nervana™ reference deep learning framework
...The gpu backend is selected by default, so the above command is equivalent to if a compatible GPU resource is found on the system. The Intel Math Kernel Library takes advantages of the parallelization and vectorization capabilities of Intel Xeon and Xeon Phi systems. When hyperthreading is enabled on the system, we recommend the following KMP_AFFINITY setting to make sure parallel threads are 1:1 mapped to the available physical cores. -
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Deep Learning with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in... -
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TensorFlow on Raspberry Pi
TensorFlow for Raspberry Pi
TensorFlow on Raspberry Pi. -
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TEES
Turku Event Extraction System
Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information. -
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AWS IoT Arduino Yún SDK
SDK for connecting to AWS IoT from an Arduino Yún
The AWS-IoT-Arduino-Yún-SDK allows developers to connect their Arduino Yún compatible Board to AWS IoT. By connecting the device to the AWS IoT, users can securely work with the message broker, rules and the Thing Shadow provided by AWS IoT and with other AWS services like AWS Lambda, Amazon Kinesis, Amazon S3, etc. The AWS-IoT-Arduino-Yún-SDK consists of two parts, which take use of the resources of the two chips on Arduino Yún, one for native Arduino IDE API access and the other for... -
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qwpr keylayout and layout translator
A keyboard layout that's worth learning.
Qwpr (pronounced "qwipper", named for the first four keys) is a keyboard layout that's easy to learn (only 11 keys move from their qwerty positions), easy to type (32% better by the Carpalx metric), practical (programmer's punctuation, arrow keys, and all major accented characters easily accessed without moving your hands off the three main rows), and very complete (over 1000 unicode characters and combinations available). The project also includes the tools I used to translate this... -
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ... -
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HYBRYD
Library written in C with Python API for IPv6 networking
This project is a rewritten of an initial project that I've called GLUE and created in 2005. I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as... -
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Unsupervised Random Forest
On-line Unsupervised Random Forest
This tool uses Random Forest and PAM to cluster observations and to calculate the dissimilarity between observations. It supports on-line prediction of new observations (no need to retrain); and supports datasets that contain both continuous (e.g. CPU load) and categorical (e.g. VM instance type) features. In particular, we use an unsupervised formulation of the Random Forest algorithm to calculate similarities and provide them as input to a clustering algorithm. For the sake of efficiency...
