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    $300 Free Credits for Your Google Cloud Projects

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    AI Agents That Actually Do the Work

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  • 1
    spaCy

    spaCy

    Industrial-strength Natural Language Processing (NLP)

    ...It comes with pretrained statistical models and word vectors, convolutional neural network models, easy deep learning integration and so much more. spaCy is the fastest syntactic parser in the world according to independent benchmarks, with an accuracy within 1% of the best available. It's blazing fast, easy to install and comes with a simple and productive API.
    Downloads: 0 This Week
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  • 2
    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: 2 This Week
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  • 3
    Neural Tangents

    Neural Tangents

    Fast and Easy Infinite Neural Networks in Python

    Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,...
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  • 4
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the...
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    Stop Cyber Threats with VM-Series Next-Gen Firewall on Azure

    Native application identity and user-based security for your Azure cloud

    Gain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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  • 5
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    ...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 tutorials and examples. Fast prototyping through highly modular built-in neural network layers, regularizers, optimizers, and 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. ...
    Downloads: 0 This Week
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  • 6
    AdaNet

    AdaNet

    Fast and flexible AutoML with learning guarantees

    AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing 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. ...
    Downloads: 1 This Week
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  • 7
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than...
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  • 8
    Feed-forward neural network for python
    ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
    Downloads: 0 This Week
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  • 9
    Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets.
    Downloads: 15 This Week
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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

    MongoDB 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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  • 10
    Yann
    Yann is Yet Another Neural Network. Yann is a library to create fast neural networks. It is also a GUI to easily create, edit, train, execute and investigate networks. Multiple topologies, runtime properties and ensemble learning are supported.
    Downloads: 0 This Week
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