Search Results for "search" - Page 3
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Showing 72 open source projects for "search"
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also... -
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run... -
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EfficientNet Keras
Implementation of EfficientNet model. Keras and TensorFlow Keras
This repository contains a Keras (and TensorFlow Keras) reimplementation of EfficientNet, a lightweight convolutional neural network architecture achieving state-of-the-art accuracy with an order of magnitude fewer parameters and FLOPS, on both ImageNet and five other commonly used transfer learning datasets. Convolutional Neural Networks (ConvNets) are commonly developed at a fixed resource budget, and then scaled up for better accuracy if more resources are available. In this paper, we... -
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AdaNet
Fast and flexible AutoML with learning guarantees
...Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each iteration, it measures the ensemble loss for each candidate, and selects the best one to move onto the next iteration. Adaptive neural architecture search and ensemble learning in a single train call. Regression, binary and multi-class classification, and multi-head task support. A tf.estimator.Estimator API for training, evaluation, prediction, and serving models. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
X-DeepLearning (XDL for short) is a complete set of deep optimization solutions for high-dimensional sparse data scenarios (such as advertising/recommendation/search, etc.). XDL version 1.2 has been released recently. Performance optimization for large batch/low concurrency scenarios, 50-100% performance improvement in such scenarios. Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. ... -
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automl-gs
Provide an input CSV and a target field to predict, generate a model
Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model... -
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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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AerinSistemas-Noname
Elasticsearch to Pandas dataframe or CSV
API and command line utility, written in Python, for querying Elasticsearch exporting result as documents into a CSV file. The search can be done using logical operators or ranges, in combination or alone. The output can be limited to the desired attributes. Also ToT can insert the querying to a Pandas Dataframe or/and save its in a HDF5 container (under development). -
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Siamese and triplet learning
Siamese and triplet networks with online triplet mining in PyTorch
...These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning. The repository demonstrates how to train these models using contrastive loss and triplet loss functions, which encourage embeddings of similar samples to be close while pushing dissimilar samples farther apart. It includes data loaders, training scripts, neural network architectures, and evaluation metrics that allow researchers to experiment with different embedding learning strategies. ... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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...In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit: http://search.maven.org/#search|ga|1|teachingbox FOR DEVELOPERS: 1) If you use Apache Maven, just add the following dependency to your pom.xml: <dependency> <groupId>org.sf.teachingbox</groupId> <artifactId>teachingbox-core</artifactId> <version>1.2.3</version> </dependency> 2) If you want to check out the most recent source-code: git clone https://git.code.sf.net/p/teachingbox/core teachingbox-core Documentation: https://sourceforge.net/p/teachingbox/documentation/HEAD/tree/trunk/manual/
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Bolt ML
10x faster matrix and vector operations
...This approach significantly reduces both memory usage and computational overhead when working with high-dimensional data commonly used in machine learning systems. Bolt is particularly useful in applications such as similarity search, approximate nearest neighbor queries, and large-scale matrix computations where millions of vectors must be processed efficiently. The project includes algorithms designed to accelerate operations such as dot products and distance calculations, which are central to many machine learning tasks. -
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GA-EoC
GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations
...To enhance classification performances, we propose an ensemble of classifiers that combine the classification outputs of base classifiers using the simplest and largely used majority voting approach. Instead of creating the ensemble using all base classifiers, we have implemented a genetic algorithm (GA) to search for the best combination from heterogeneous base classifiers. The classification performances achieved by the proposed method method on the chosen datasets are promising. -
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Intelligent Keyword Miner
Intelligent SEO keyword miner and predicing tool
THIS IS A NETBEANS 8.02 PROJECT ENGLISH ONLY This program was made to help me with the patent research. It simply generates the search keywords, based on your upvotes or a downvotes of the input parameters. It can accept a text or URL (text takes a prescedence over the URL). If you input URL, it goes to a page, and learns its text from HTML format. This program is intelligent as it predicts what you may want to search next, based on your personal trends. After searching the suggestions, you can choose to reset or train it further. ... -
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Reactor Breeder
A Genetic Algorithm for Reactors in StarMade
...This mechanism leads to difficulties in getting maximal power generation out of such reactors. This program rectifies this issue by using a self-organizing variant of brute force search. Much of the search space is pruned early on by a user-selectable fitness function. Within a few epochs, reactor output quickly converges to several sub-optimal, yet high-output reactors. Given enough time, the idea is that the optimal reactor configuration will be yielded. -
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Large Scale Optimization Templates
C++ templates with generic nonlinear optimization algorithms
Highly tunable, simple to use collection of the templates, containing a set of classes for solving unconstrained large scale nonlinear optimization problems. Currently it contains: -- Limited Memory Quasi Newton (L-BFSG) -- BFSG -- Conjugate Gradient -- Gradient Descent -- Wolf condition Line Search -- Backtracking Line Search -- Exact Golden Search -- Golden Search with Wolf condition We also distribute a set of tests with the library. -
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TreeLiker
TreeLiker is a collection of fast algorithms for working with complex
...The data can, for example, describe large organic molecules such as proteins or groups of individuals such as social networks or predator-prey networks etc. The algorithms included in TreeLiker are unique in that, in principle, they are able to search given sets of relational patterns exhaustively, thus guaranteeing that if some good pattern capturing an important feature of the problem exists, it will be found. In experiments with real-life data, the algorithms were shown to be able to construct complete non-redundant sets of patterns for chemical datasets involving several thousands of molecules as well as for comparably large datasets from genomics or proteomics. ... -
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Clever Algorithms
Clever Algorithms: Nature-Inspired Programming Recipes
...Each entry follows a consistent template: motivation, strategy, pseudocode, parameter choices, variations, and references, making it easy to compare approaches. The catalog spans evolutionary algorithms, swarm intelligence, immune systems, simulated annealing, tabu search, and other metaheuristics, plus guidance on when and how to tune them. Example implementations and worked problems show how to encode solutions, define fitness, and balance exploration with exploitation. The emphasis is on pragmatism—enough theory to understand why an algorithm works, and enough detail to get it running in your environment. ... -
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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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HSSVM(Hyper-Sphere Support Vector Machines) is a software for solving multi-classification problem, implemented by Java.
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SURIKATA (Syntactic Universal Reasoning for Inducing Kolmogorov Abstract Theories Automatically) is a system for searching large spaces of artifacts and inducing algorithms for generating similar artifacts.
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Spider that recollects data from MySpace Social Network. At now, it is only designed to extract information from native american people because it is used for a social science study in the UNAM (Universidad Nacional Autónoma de México).
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Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.
