Results for: edmonds-karp algorithm implementation in python

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Algorithmic Trading Software
Algorithmic trading software enhances and automates trading capabilities for trading financial instruments such as equities, securities, digital assets, currency, and more. Algorithmic trading software, also known as algo trading software or automated trading software, enables the automatic execution of trades depending on occurrences of specified criteria, indicators, and movements by connecting with a broker or exchange.
Mentoring Software
Mentoring software is a type of software designed to facilitate the mentor-mentee relationship. It provides users with tools for scheduling, tracking progress, providing feedback, and developing plans for growth. The software can be used as a standalone system or integrated into existing enterprise solutions. Mentoring software allows organizations to easily manage and monitor their mentorship programs remotely and efficiently.
Data Science Software
Data science software is a collection of tools and platforms designed to facilitate the analysis, interpretation, and visualization of large datasets, helping data scientists derive insights and build predictive models. These tools support various data science processes, including data cleaning, statistical analysis, machine learning, deep learning, and data visualization. Common features of data science software include data manipulation, algorithm libraries, model training environments, and integration with big data solutions. Data science software is widely used across industries like finance, healthcare, marketing, and technology to improve decision-making, optimize processes, and predict trends.
Identity Resolution Software
Identity resolution software enables organizations to identify and track the identity of customers, users, or potential customers across multiple devices and services. Identity resolution solutions are very helpful for running personalized campaigns across different channels and devices.
Augmented Reality Software
Augmented reality software is used to create interactive computer-generated 3D models and simulations that can be projected and manipulated.
Computer Vision Software
Computer vision software allows machines to interpret and analyze visual data from images or videos, enabling applications like object detection, image recognition, and video analysis. It utilizes advanced algorithms and deep learning techniques to understand and classify visual information, often mimicking human vision processes. These tools are essential in fields like autonomous vehicles, facial recognition, medical imaging, and augmented reality, where accurate interpretation of visual input is crucial. Computer vision software often includes features for image preprocessing, feature extraction, and model training to improve the accuracy of visual analysis. Overall, it enables machines to "see" and make informed decisions based on visual data, revolutionizing industries with automation and intelligence.
Advanced Distribution Management Systems (ADMS)
Advanced Distribution Management Systems (ADMS) is a suite of integrated, digital tools for power utility companies. It enables utilities to monitor and control their networks in ways that weren’t previously possible. ADMS provides an overall operational picture of the grid along with increased visualization of current system conditions. This data, in addition to real-time analytics, helps utilities make more informed decisions about the operation and maintenance of their networks. Furthermore, ADMS allows for effective forecasting and asset management as well as energy trading capabilities. By having this advanced technology in place, power distribution can be optimized while reducing cost and increasing safety.
AI Coding Assistants
AI coding assistants are software tools that use artificial intelligence to help developers write, debug, and optimize code more efficiently. These assistants typically offer features like code auto-completion, error detection, suggestion of best practices, and code refactoring. AI coding assistants often integrate with integrated development environments (IDEs) and code editors to provide real-time feedback and recommendations based on the context of the code being written. By leveraging machine learning and natural language processing, these tools can help developers increase productivity, reduce errors, and learn new programming techniques.
Customer Onboarding Software
Customer onboarding software helps businesses guide new customers through the setup, activation, and adoption of their products or services. It provides structured workflows, checklists, and progress tracking to ensure every customer receives a consistent onboarding experience. Many platforms include automated emails, in-app guidance, task reminders, and personalized content to improve engagement and reduce time-to-value. The software also offers analytics to help teams monitor customer health and identify bottlenecks in the onboarding process. Overall, customer onboarding software improves satisfaction, accelerates product adoption, and supports long-term customer success.
Change Management Software
Change management software is a tool used to coordinate changes and improve the effectiveness of varying processes. It enables organizations to track and manage change requests, assess impact, approve or reject change proposals, assign tasks to relevant personnel, and monitor progress until completion. Change management software also allows users to document all changes for audit and compliance purposes. Additionally, it provides notifications and automated workflows which simplify the process of adapting to organizational change. Finally, the software can enable collaboration between team members by providing them with access to data stored in one central repository.
Natural Language Generation Software
Natural language generation software is computer-generated software designed to create natural-sounding output. It can generate text from structured data sources such as databases, or from unstructured sources like audio or video recordings. The output of this software can be used for various tasks such as summarizing information or producing news articles. Natural language generation technology is commonly used in applications that require automated content creation and natural language processing algorithms.
Product Recommendation Engines
Product recommendation engines use algorithms and customer data to suggest personalized products to users based on their browsing behavior, past purchases, or preferences. These platforms analyze large sets of data, such as customer interactions and purchase history, to identify patterns and recommend products that are most likely to interest the individual customer. Product recommendation engines help e-commerce businesses increase sales and customer engagement by offering a more personalized shopping experience. By integrating these engines, businesses can provide relevant suggestions, improve conversion rates, and enhance customer satisfaction.
Code Search Engines
Code search engines are specialized search tools that allow developers to search through codebases, repositories, or libraries to find specific functions, variables, classes, or code snippets. These tools are designed to help developers quickly locate relevant parts of code, analyze code quality, and identify reusable components. Code search engines often support various programming languages, providing search capabilities like syntax highlighting, filtering by file types or attributes, and even advanced search options using regular expressions. They are particularly useful for navigating large codebases, enhancing code reuse, and improving overall productivity in software development projects.
Artificial Intelligence Software
Artificial Intelligence (AI) software is computer technology designed to simulate human intelligence. It can be used to perform tasks that require cognitive abilities, such as problem-solving, data analysis, visual perception and language translation. AI applications range from voice recognition and virtual assistants to autonomous vehicles and medical diagnostics.
Deep Learning Software
Deep learning software provides tools and frameworks for developing, training, and deploying artificial neural networks, particularly for complex tasks such as image and speech recognition, natural language processing (NLP), and autonomous systems. These platforms leverage large datasets and powerful computational resources to enable machines to learn patterns and make predictions. Popular deep learning software includes frameworks like TensorFlow, PyTorch, Keras, and Caffe, which offer pre-built models, libraries, and tools for designing custom models. Deep learning software is essential for industries that require advanced AI solutions, including healthcare, finance, automotive, and entertainment.
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  • 1
    MatConvNet
    The VLFeat open source library implements popular computer vision algorithms specializing in image understanding and local features extraction and matching. Algorithms include Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, large scale SVM training, and many others. It is written in C for efficiency and compatibility, with interfaces in MATLAB for ease of use, and detailed documentation throughout. ...
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  • 2
    Neuri

    Neuri

    Neuri

    We conduct and implement cutting-edge research on artificial intelligence to create real advantage in financial investment. Illuminating the financial market with ground-breaking neuro-prediction. We combine novel deep reinforcement learning algorithms and graph-based learning with artificial neural networks for modeling and predicting time series. Neuri strives to generate synthetic data emulating the global financial markets, testing it with complex simulations of trading behavior. ...
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  • 3
    Ray

    Ray

    Anyscale

    Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries.
    Starting Price: Free
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  • 4
    NVIDIA DeepStream SDK
    ...DeepStream is integral to NVIDIA Metropolis, a platform for building end-to-end services that transform pixel and sensor data into actionable insights. The SDK offers a powerful and flexible environment suitable for a wide range of industries, supporting multiple programming options such as C/C++, Python, and Graph Composer's intuitive UI. It allows for real-time insights by understanding rich, multi-modal sensor data at the edge and supports managed AI services through deployment in cloud-native containers orchestrated with Kubernetes.
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  • 5
    Microsoft Cognitive Toolkit
    ...CNTK allows the user to easily realize and combine popular model types such as feed-forward DNNs, convolutional neural networks (CNNs) and recurrent neural networks (RNNs/LSTMs). CNTK implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK can be included as a library in your Python, C#, or C++ programs, or used as a standalone machine-learning tool through its own model description language (BrainScript). In addition you can use the CNTK model evaluation functionality from your Java programs. ...
    3 Ratings
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  • 6
    IBM Watson Machine Learning Accelerator
    Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. ...
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  • 7
    DataMelt

    DataMelt

    jWork.ORG

    ...Unlike other statistical programs, it is not limited to a single programming language. This software combines the world's most-popular enterprise language, Java, with the most popular scripting language used in data science, such as Jython (Python), Groovy, JRuby.
    Starting Price: $0
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  • 8
    Horovod

    Horovod

    Horovod

    Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.
    Starting Price: Free
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  • 9
    Deeplearning4j

    Deeplearning4j

    Deeplearning4j

    ...Deeplearning4j is written in Java and is compatible with any JVM language, such as Scala, Clojure, or Kotlin. The underlying computations are written in C, C++, and Cuda. Keras will serve as the Python API. Eclipse Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Apache Spark, DL4J brings AI to business environments for use on distributed GPUs and CPUs. There are a lot of parameters to adjust when you're training a deep-learning network. ...
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  • 10
    MXNet

    MXNet

    The Apache Software Foundation

    ...Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. ...
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  • 11
    VisionPro Deep Learning
    VisionPro Deep Learning is the best-in-class deep learning-based image analysis software designed for factory automation. Its field-tested algorithms are optimized specifically for machine vision, with a graphical user interface that simplifies neural network training without compromising performance. VisionPro Deep Learning solves complex applications that are too challenging for traditional machine vision alone, while providing a consistency and speed that aren’t possible with human inspection. ...
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  • 12
    SKY ENGINE

    SKY ENGINE

    SKY ENGINE AI

    SKY ENGINE AI is a simulation and deep learning platform that generates fully annotated, synthetic data and trains AI computer vision algorithms at scale. The platform is architected to procedurally generate highly balanced imagery data of photorealistic environments and objects and provides advanced domain adaptation algorithms. SKY ENGINE AI platform is a tool for developers: Data Scientists, ML/Software Engineers creating computer vision projects in any industry. ...
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  • 13
    IntelliHub

    IntelliHub

    Spotflock

    ...It can also do clustering and visualize different clusters. It supports multiple ML libraries like Weka, Scikit-Learn, H2O and Tensorflow. It includes around 22 different algorithms for building classification, regression and clustering models.
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  • 14
    Alfi

    Alfi

    Alfi

    Alfi, Inc. engages in creating interactive digital out-of-home advertising experiences. Alfi utilizes artificial intelligence and computer vision to better serve ads to people. Alfi’s proprietary Ai algorithm understands small facial cues and perceptual details that make potential customers a good candidate for a particular product. The automation works in a way that respects user privacy; without tracking, storing cookies, or using identifiable personal information. Ad agencies are empowered to examine real-time analytics data including interactive experiences, engagement, sentiment, and click-through rate that are otherwise unavailable to out-of-home advertisers. ...
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  • 15
    Strong Analytics

    Strong Analytics

    Strong Analytics

    Our platforms provide a trusted foundation upon which to design, build, and deploy custom machine learning and artificial intelligence solutions. Build next-best-action applications that learn, adapt, and optimize using reinforcement-learning based algorithms. Custom, continuously-improving deep learning vision models to solve your unique challenges. Predict the future using state-of-the-art forecasts. Enable smarter decisions throughout your organization with cloud based tools to monitor and analyze. The process of taking a modern machine learning application from research and ad-hoc code to a robust, scalable platform remains a key challenge for experienced data science and engineering teams. ...
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  • 16
    Neural Designer
    ...It provides a user-friendly interface that allows users to build, train, and evaluate neural networks without requiring extensive programming knowledge. With a wide range of features and algorithms, Neural Designer simplifies the entire machine learning workflow, from data preprocessing to model optimization. In addition, it supports various data types, including numerical, categorical, and text, making it versatile for domains. Additionally, Neural Designer offers automatic model selection and hyperparameter optimization, enabling users to find the best model for their data with minimal effort. ...
    2 Ratings
    Starting Price: $2495/year (per user)
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  • 17
    Darwin

    Darwin

    SparkCognition

    Darwin is an automated machine learning product that enables your data science and business analytics teams to move more quickly from data to meaningful results. Darwin helps organizations scale the adoption of data science across teams, and the implementation of machine learning applications across operations, becoming data-driven enterprises.
    Starting Price: $4000
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  • 18
    TFLearn

    TFLearn

    TFLearn

    ...It was designed to provide a higher-level API to TensorFlow in order to facilitate and speed up experimentations while remaining fully transparent and compatible with it. Easy-to-use and understand high-level API for implementing deep neural networks, with tutorial and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, metrics. Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. ...
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  • 19
    Determined AI

    Determined AI

    Determined AI

    ...Our open source deep learning platform enables you to train models in hours and minutes, not days and weeks. Instead of arduous tasks like manual hyperparameter tuning, re-running faulty jobs, and worrying about hardware resources. Our distributed training implementation outperforms the industry standard, requires no code changes, and is fully integrated with our state-of-the-art training platform. With built-in experiment tracking and visualization, Determined records metrics automatically, makes your ML projects reproducible and allows your team to collaborate more easily. Your researchers will be able to build on the progress of their team and innovate in their domain, instead of fretting over errors and infrastructure.
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  • 20
    Analance
    ...It is built to deliver core analytical processing power to ensure data insights are accessible to everyone, performance remains consistent as the system grows, and business objectives are continuously met within a single platform. Analance is focused on turning quality data into accurate predictions allowing both data scientists and citizen data scientists with point and click pre-built algorithms and an environment for custom coding. Company – Overview Ducen IT helps Business and IT users of Fortune 1000 companies with advanced analytics, business intelligence and data management through its unique end-to-end data science platform called Analance.
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  • 21
    NetApp AIPod
    ...By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and inference, while ensuring robust data management and security. With preconfigured infrastructure optimized for AI tasks, NetApp AIPod reduces complexity, accelerates time to insights, and supports seamless integration into hybrid cloud environments.
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