Search Results for "combine" - Page 5
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Showing 140 open source projects for "combine"
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Bandwidth
Monitor monthly internet Transmit and Receive bandwidth usage - Linux
Keep track of bandwidth usage Allows Linux users to monitor their Transmit and Receive bandwidth usage with a simple text based menu, via your browser or from the command line. Some of us are unable to get "unlimited", "all that you can eat", internet packages and are left trying to stay within our Download/Upload limits, whilst paying dearly for the "privilege". Equally, we didn't have the foresight or the money to purchase an snmp managed router, so we are unable to strip the traffic... -
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Thesa
It is a Platform to connect to tryton (json-rpc) and is based on qt
...Tabs are created with qml files and can be loaded locally from a folder or from trytond using thesamodule (https://github.com/numaelis/thesamodule). Thesa's goal is to be able to combine tryton with Qt / Qml, for special cases such as using the opengl performance of qml2 Requirements: pyside2 5.12 or higher: https://download.qt.io/official_releases/QtForPython/pyside2/ Run: python3 main.py you can find source code in: https://github.com/numaelis/thesa -
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AstroCamera
Raspberry Pi with HQ Camera for Astro Photography
Combine a Raspberry Pi 3 B+ with the HQ Camera (12 Megapixel). Make astronomical Photos and Videos with the Camera. -
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FARM
Fast & easy transfer learning for NLP
...AMP optimizers (~35% faster) and parallel preprocessing (16 CPU cores => ~16x faster). Modular design of language models and prediction heads. Switch between heads or combine them for multitask learning. Full Compatibility with HuggingFace Transformers' models and model hub. Smooth upgrading to newer language models. Integration of custom datasets via Processor class. Powerful experiment tracking & execution. -
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Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot... -
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Opyrator
Turns your machine learning code into microservices with web API
Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python... -
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MLOps Course
Learn how to design, develop, deploy and iterate on ML apps
The MLOps Course by Goku Mohandas is an open-source curriculum that teaches how to combine machine learning with solid software engineering to build production-grade ML applications. It is structured around the full lifecycle: data pipelines, modeling, experiment tracking, deployment, testing, monitoring, and iteration. The repository itself contains configuration, code examples, and links to accompanying lessons hosted on the Made With ML site, which provide detailed narrative explanations and diagrams. ... -
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Pydub
Manipulate audio with a simple and easy high level interface
...Note that no validation takes place on these parameters, and you may be limited by what your particular build of ffmpeg/avlib supports. You can open and save WAV files with pure python. For opening and saving non-wav files, like mp3, you'll need ffmpeg or libav. Any operations that combine multiple AudioSegment objects in any way will first ensure that they have the same number of channels, frame rate, sample rate, bit depth, etc. -
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Vector AI
A platform for building vector based applications
...The backbone of many popular A.I use cases like reverse image search, recommendations, personalization, etc. There are scenarios where vector search is not as effective as traditional search, e.g. searching for skus. Vector AI lets you combine vector search with all the features of traditional search such as filtering, fuzzy search, and keyword matching to create an even more powerful search. -
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Soma-direct
System Omnichannel Marketing Analysis
Soma - System Omnichannel Marketing Analysis is an open-source solution for simplifying the processes of analyzing and predicting consumer behavior. With Soma, you can combine data from multiple systems and channels in the profile joining process. Interactions and behaviors registered as a part of a unique user create and show what a Customer Journey looks like. The data is subjected to an analysis process which enables the examination of the significance of individual touchpoints for the purchasing process. -
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TFKit
Handling multiple nlp task in one pipeline
...It leverages the use of transformers on many tasks with different models in this all-in-one framework. All you need is a little change of config. You can use tfkit for model training and evaluation with tfkit-train and tfkit-eval. The key to combine different task together is to make different task with same data format. All data will be in csv format - tfkit will use csv for all task, normally it will have two columns, first columns is the input of models, the second column is the output of models. Plane text with no tokenization - there is no need to tokenize text before training, or do re-calculating for tokenization, tfkit will handle it for you. ... -
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights, biases, activation functions, and gradient descent, as well as more advanced techniques like convolutional networks, recurrent networks, and reinforcement learning. ... -
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CBMPy
PySCeS Constraint Based Modelling
PySCeS CBMPy is a new platform for constraint based modelling and analysis. It has been designed using principles developed in the PySCeS simulation software project: usability, flexibility and accessibility. CBMPy supports the latest standards for encoding CBM models encoding, SBML L3 FBC, COBRA as well as MIRIAM compliant RDF and custom annotations. Its architecture is both extensible and flexible using data structures that are intuitive to the biologist while transparently... -
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imgaug
Image augmentation for machine learning experiments
imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. ... -
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Texar
Toolkit for Machine Learning, Natural Language Processing
...A mirror of this repository is maintained by Petuum Open Source. Two Versions, (Mostly) Same Interfaces. Texar-TensorFlow (this repo) and Texar-PyTorch have mostly the same interfaces. Both further combine the best design of TF and PyTorch. Rich Pre-trained Models, Rich Usage with Uniform Interfaces. BERT, GPT2, XLNet, etc, for encoding, classification, generation, and composing complex models with other Texar components! -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
...Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. The codebase is organized as modular math and finance primitives so you can combine building blocks or target end-to-end examples. It includes Bazel builds, tests, and example notebooks to accelerate learning and adoption in real workflows. With hardware acceleration and differentiable models, it enables modern techniques like gradient-based calibration and end-to-end learning of market dynamics. -
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Offensive Web Testing Framework
Offensive Web Testing Framework (OWTF), is a framework
OWASP OWTF is a project focused on penetration testing efficiency and alignment of security tests to security standards like the OWASP Testing Guide (v3 and v4), the OWASP Top 10, PTES and NIST so that pentesters will have more time to see the big picture and think out of the box. More efficiently find, verify and combine vulnerabilities. Have time to investigate complex vulnerabilities like business logic/architectural flaws or virtual hosting sessions. Perform more tactical/targeted fuzzing on seemingly risky areas. Demonstrate true impact despite the short timeframes we are typically given to test. The tool is highly configurable and anybody can trivially create simple plugins or add new tests in the configuration files without having any development experience. ... -
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DACO-algorithm
A novel transcription factor complex prediction algorithm.
Eukaryotic gene expression is controlled through molecular logic circuits that combine regulatory signals of many different factors. Complexation of transcription factors and other regulatory proteins is a prevailing and highly conserved mechanism of signal integration within critical regulatory pathways and enable to infer controlled genes as well as the exerted regulatory mechanism. We developed DACO (domain-aware cohesiveness optimization), a novel algorithm that combines protein-protein interaction networks and domain-domain interaction networks with the cluster-quality metric cohesiveness. ... -
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AI learning
AiLearning, data analysis plus machine learning practice
...Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. The number of Github Stars exceeds 60k, and it ranks in the top 100 of all Github organizations. ... -
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haxor-news
Browse Hacker News like a haxor
haxor-news brings Hacker News to the terminal, allowing you to view/filter the following without leaving your command line; posts, post comments, post-linked web content, monthly hiring and freelancers posts, user info, and onions. haxor-news helps you filter the large number of comments that popular posts generate. Job hunting or just curious what's out there? Filter the monthly who's hiring and freelancers post. Combine haxor-news with pipes, redirects, and other command-line utilities. Output to pagers, write to files, automate with cron, etc. haxor-news comes with a handy optional auto-completer with interactive help. After viewing a list of posts, you can view a post's linked web content by referencing the post #. The HTML contents of the post's link are formatted for easy viewing within your terminal. ... -
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PyDaMelo
Python-compatible Data mining elementary objects
An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks. -
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ElastAlert
Easy and flexible alerting with ElasticSearch
...This is configured by a set of rules, each of which defines a query, a rule type, and a set of alerts. Several rule types with common monitoring paradigms are included with ElastAlert. Alerts link to Kibana dashboards. Aggregate counts for arbitrary fields. Combine alerts into periodic reports. Separate alerts by using a unique key field. Intercept and enhance match data. Additional rule types and alerts can be easily imported or written. -
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MacroFusion
GUI to combine photos to get deeper DOF or HDR.
MacroFusion is a neat little GUI for great tool Enfuse (command line). It makes easy fusion few photos to one with great DOF (Deep of Field) or DR (Dynamic Range). It can be useful for every macro lovers or landscapers. -
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Mi-perf
Miperf is an automated enhancement of iperf tool
iperf is a tool that can create TCP&UDP data streams and measure the throughput of a network that is carrying them. basically to do this iperf testing, we need 2 machines to act as server and client. we run a command -s in server side and then launch a client connection to a server by typing a command -c in client side. before that we need to enter the webgui of the wifi AP to do some configurations such as, change the frequency mode and channel. so we need to repeat the same process/steps for next test cases.imagine if we have hundred test cases, how much time we have to spend for this testing. To address this problem, i have come out with this tool which is called Mi-perfv2.0. miperf is an automated enhancement of iperf tool which combine many activities in a pyhton script. it contains selenium, iperf,wifi profile and also integration with jenkins. we only need to type a line of command, then miperf will run the test for hundred test cases by itself and displays result in a table
