Showing 9 open source projects for "security"

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  • 1
    Python Outlier Detection

    Python Outlier Detection

    A Python toolbox for scalable outlier detection

    PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural...
    Downloads: 7 This Week
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  • 2
    PaddleX

    PaddleX

    PaddlePaddle End-to-End Development Toolkit

    PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the...
    Downloads: 7 This Week
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  • 3
    MNN

    MNN

    MNN is a blazing fast, lightweight deep learning framework

    ...At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity distribution, security risk control. In addition, MNN is also used on embedded devices, such as IoT. MNN Workbench could be downloaded from MNN's homepage, which provides pretrained models, visualized training tools, and one-click deployment of models to devices. Android platform, core so size is about 400KB, OpenCL so is about 400KB, Vulkan so is about 400KB. ...
    Downloads: 15 This Week
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  • 4
    Amazon SageMaker Examples

    Amazon SageMaker Examples

    Jupyter notebooks that demonstrate how to build models using SageMaker

    ...It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies easy on-boarding for their team members, freeing them up from complex systems admin and security processes. Administrators control data access and resource provisioning for their users. Notebook Instances are another option. They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK.
    Downloads: 0 This Week
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  • 5
    FATE

    FATE

    An industrial grade federated learning framework

    ...FedAI is a community that helps businesses and organizations build AI models effectively and collaboratively, by using data in accordance with user privacy protection, data security, data confidentiality and government regulations.
    Downloads: 0 This Week
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  • 6
    Adaptive Intelligence

    Adaptive Intelligence

    Adaptive Intelligence also known as "Artificial General Intelligence"

    Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills.
    Downloads: 6 This Week
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  • 7
    T81 558

    T81 558

    Applications of Deep Neural Networks

    ...This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids.
    Downloads: 0 This Week
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  • 8
    Face Mask Detection

    Face Mask Detection

    Face Mask Detection system based on computer vision and deep learning

    Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential...
    Downloads: 0 This Week
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  • 9
    PassGAN

    PassGAN

    A Deep Learning Approach for Password Guessing

    ...The maintainer also documented experimental results and questioned how the approach compared with established RNN and Markov methods. Because generated candidates can be used in password-recovery attacks, the software is most appropriate for authorized security research and password-strength analysis.
    Downloads: 4 This Week
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