Showing 45 open source projects for "prediction"

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  • 1
    Stock prediction deep neural learning

    Stock prediction deep neural learning

    Predicting stock prices using a TensorFlow LSTM

    ... is a complex task, as it is influenced by various factors such as market trends, political events, and economic indicators. The fluctuations in stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction.
    Downloads: 2 This Week
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  • 2
    DeepCTR

    DeepCTR

    Package of deep-learning based CTR models

    ... techniques have been widely used in CTR prediction task. The data in CTR estimation task usually includes high sparse,high cardinality categorical features and some dense numerical features. Since DNN are good at handling dense numerical features,we usually map the sparse categorical features to dense numerical through embedding technique.
    Downloads: 1 This Week
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  • 3
    KServe

    KServe

    Standardized Serverless ML Inference Platform on Kubernetes

    ... Rollouts to your ML deployments. It enables a simple, pluggable, and complete story for Production ML Serving including prediction, pre-processing, post-processing and explainability. KServe is being used across various organizations.
    Downloads: 1 This Week
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  • 4
    Visual Studio Code client for Tabnine

    Visual Studio Code client for Tabnine

    Visual Studio Code client for Tabnine

    ...-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, content assist, unit test generation or documentation generation, using Tabnine can massively impact your coding velocity, significantly cutting down your coding time.
    Downloads: 1 This Week
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    Contract Automation Made Easy

    Use Docubee to easily gather data, generate contracts, share them your way, and collect secure eSignatures

    Docubee is an intelligent contract automation platform that allows you to quickly and painlessly generate, manage, share, and sign contracts. Featuring powerful conditional logic-based workflows, generative AI technology, and an easily adaptable interface, Docubee makes it easy to automate your most complex contracts and agreements.
  • 5
    Gorse Recommender System Engine

    Gorse Recommender System Engine

    An open source recommender system service written in Go

    An open-source recommender system service written in Go. Recommend items from Popular, latest, user-based, item-based and collaborative filtering. Search the best recommendation model automatically in the background. Support horizontal scaling in the recommendation stage after single node training. Support Redis, MySQL, Postgres, MongoDB, and ClickHouse as its storage backend. Expose RESTful APIs for data CRUD and recommendation requests. Analyze online recommendation performance from...
    Downloads: 1 This Week
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  • 6
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical...
    Downloads: 1 This Week
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  • 7
    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: 1 This Week
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  • 8
    cAdvisor

    cAdvisor

    Analyzes resource usage and performance characteristics

    cAdvisor (Container Advisor) provides container users an understanding of the resource usage and performance characteristics of their running containers. It is a running daemon that collects, aggregates, processes, and exports information about running containers. Specifically, for each container it keeps resource isolation parameters, historical resource usage, histograms of complete historical resource usage and network statistics. This data is exported by container and machine-wide....
    Downloads: 1 This Week
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  • 9
    frugally-deep

    frugally-deep

    A lightweight header-only library for using Keras (TensorFlow) models

    Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run...
    Downloads: 0 This Week
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    Automated RMM Tools | RMM Software

    Proactively monitor, manage, and support client networks with ConnectWise Automate

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  • 10
    tsfresh

    tsfresh

    Automatic extraction of relevant features from time series

    tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python....
    Downloads: 0 This Week
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  • 11
    UnionML

    UnionML

    Build and deploy machine learning microservices

    ... learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. This helps you maintain consistent code across your ML stack, from training to prediction logic.
    Downloads: 0 This Week
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  • 12
    Alphafold

    Alphafold

    Open source code for AlphaFold

    This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper. Please also refer to the Supplementary Information for a detailed description of the method. You can use...
    Downloads: 0 This Week
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  • 13
    OmegaT - multiplatform CAT tool

    OmegaT - multiplatform CAT tool

    The free computer aided translation (CAT) tool for professionals

    OmegaT is a free and open source multiplatform Computer Assisted Translation tool with fuzzy matching, translation memory, keyword search, glossaries, and translation leveraging into updated projects.
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    Downloads: 1,763 This Week
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  • 14
    m2cgen

    m2cgen

    Transform ML models into a native code

    m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase...
    Downloads: 0 This Week
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  • 15
    Gemi

    Gemi

    PCR primers / probes design from multiple & degenerate sequences

    ... PCR (qPCR, rt-PCR, etc.), and Sanger sequencing. Gemi can parse large dataset of sequences efficiently. Article: Gemi: PCR primers prediction from multiple alignments Comparative and functional genomics 2012;2012:783138 DOI: https://doi.org/10.1155/2012/783138 PMID: https://www.ncbi.nlm.nih.gov/pubmed/23316117 PMCID: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3535827/
    Downloads: 1 This Week
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  • 16
    LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
    Downloads: 0 This Week
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  • 17
    TransPose

    TransPose

    PyTorch Implementation for "TransPose, Keypoint localization

    TransPose is a human pose estimation model based on a CNN feature extractor, a Transformer Encoder, and a prediction head. Given an image, the attention layers built in Transformer can efficiently capture long-range spatial relationships between keypoints and explain what dependencies the predicted keypoints locations highly rely on.
    Downloads: 0 This Week
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  • 18
    Tabnine

    Tabnine

    Vim client for TabNine

    Tabnine is an AI-powered code completion extension trusted by millions of developers around the world. Whether you’re just getting started as a developer or if you’ve been doing it for decades, Tabnine will help you code twice as fast with half the keystrokes – all in your favorite IDE. Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or content...
    Downloads: 7 This Week
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  • 19
    AdaNet

    AdaNet

    Fast and flexible AutoML with learning guarantees

    ... 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.
    Downloads: 1 This Week
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  • 20
    DETR

    DETR

    End-to-end object detection with transformers

    PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based...
    Downloads: 1 This Week
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  • 21
    Fun4Me

    Fun4Me

    A package for functional annotation for metagenomes

    This package includes a few programs for rapid functional annotation for metagenomic sequences, including, 1) Gene prediction by FragGeneScan; 2) Similarity search by RAPSearch2; 3) Functional annotation in GO (Gene Ontology) and EC (Enzyme Commission) based on similarity search results; 4) From EC to metabolic pathway reconstruction by MinPath. Inputs: Just sequencing reads (or assemblies) Outputs: Protein-coding genes (or gene fragments); similarity search; functional annotations...
    Downloads: 0 This Week
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  • 22
    MLBox

    MLBox

    MLBox is a powerful Automated Machine Learning python library

    MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make...
    Downloads: 1 This Week
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  • 23
    captcha_break

    captcha_break

    Identification codes

    This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. It supports image verification...
    Downloads: 0 This Week
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  • 24
    Skater

    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...
    Downloads: 0 This Week
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  • 25
    The Edge Machine Learning library

    The Edge Machine Learning library

    Machine learning algorithms for edge devices

    Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.These algorithms can train models for classical supervised learning problems with memory requirements that are orders...
    Downloads: 0 This Week
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