Search Results for "adam"
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Showing 56 open source projects for "adam"
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Blade Heroicons
A package to easily make use of Heroicons in your Laravel Blade views
A package to easily make use of Heroicons in your Laravel Blade views. For a full list of available icons see the SVG directory or preview them at heroicons.com. Heroicons are originally developed by Steve Schoger and Adam Wathan. -
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The Magic of CSS
A CSS course to turn you into a magician
Magic of CSS is an open source educational project by Adam Schwartz that explores advanced CSS concepts through practical lessons. It is structured as a series of chapters that cover topics like the box model, layouts, positioning, typography, and animations. The repository is designed to go beyond basic CSS tutorials, teaching how to harness the language for complex, responsive, and visually appealing designs. -
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ggml
Tensor library for machine learning
ggml is an open-source tensor library designed for efficient machine learning computation with a focus on running models locally and with minimal dependencies. Written primarily in C and C++, the library provides low-level tensor operations and automatic differentiation that allow developers to implement machine learning algorithms and neural networks efficiently. The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware... -
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neural-style in TensorFlow
Neural style in TensorFlow
...It creates a new image by combining the content of one image with the artistic style of one or more style images. The project uses TensorFlow automatic differentiation and the Adam optimizer rather than the original L-BFGS approach. Users can run it from the command line by providing a content image, style image inputs, and an output path. It supports checkpoint outputs, iteration control, style blending, and hyperparameter tuning for content weight, style weight, and learning rate. Overall, it is a focused research-style image generation tool for experimenting with artistic transfer and visual optimization. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Smart Submission Dataset Viewer
A smart viewer for inspecting (and more) CDISC submission files
The "Smart Submission Dataset Viewer" allows to inspect CDISC SDTM, SEND and ADaM submission files in the modern CDISC Dataset-JSON 1.1 standard format. The "Smart Submission Dataset Viewer" has many features that go far beyond what reviewers at the regulatory authorities usually have available, this thanks to the use of the modern CDISC Dataset-JSON format (regulatory authorities still use the outdated XPT - Transport 5 - format). -
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DeepSee
Visualize deep ocean biogeochemical sediment samples in 2D and 3D!
...🦑🦀🐚 🚀 For a live demo, visit: https://www.its.caltech.edu/~datavis/deepsee/ 🌱 To get started, visit our Wiki: https://sourceforge.net/p/deepsee/wiki/Home/ 🧑💻 To modify DeepSee for your own project, visit our GitHub repository: https://github.com/orphanlab/DeepSee/ --- Created by Adam Coscia, Haley M. Sapers, Noah Deutsch, Malika Khurana, John S. Magyar, Sergio A. Parra, Daniel R. Utter, Rebecca L. Wipfler, David W. Caress, Eric J. Martin, Jennifer B. Paduan, Maggie Hendrie, Santiago Lombeyda, Hillary Mushkin, Alex Endert, Scott Davidoff, and Victoria J. Orphan. Copyright (c) 2022-23 California Institute of Technology ("Caltech"). ... -
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spaGO
Self-contained Machine Learning and Natural Language Processing lib
A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. In other words, it has "zero dependencies", and we are committed to keeping it that way as much as possible. Spago uses a multi-module workspace to... -
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Code Maat
A command line tool to mine and analyze data from version-control
Code Maat is a command-line tool for analyzing version-control systems (Git, SVN, etc.) to uncover code health insights—development hotspots, author coupling, and temporal change metrics. Created by Adam Tornhill, it supports research in behavioral code analysis and is often paired with his books like Code as a Crime Scene and Software Design X‑Rays. -
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freeRTOS & libraries for AVR ATmega
freeRTOS for Arduino Uno, Goldilocks 1284p & Mega 2560
AVR ATmega port of freeRTOS A port of freeRTOS which can be flexibly flexibly configured use almost any available Timer on AVR ATmega devices and will operate with almost any classic Arduino device from Arduino, SeeedStudio, Sparkfun, Freetronics or Pololu. Going forward this repository will be updated less often and only with major releases. Please check at Github for the latest commits. https://github.com/feilipu/avrfreertos The Goldilocks Analogue story is told here.... -
MongoDB Atlas runs apps anywhereMongoDB 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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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
...It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target count statistics, learning rate scheduling with step and cosine options, and optimizer selection between Adam and SGD. It also includes adaptive learning rate adjustment based on batch size, image cropping, many configurable parameters, and expanded comments for easier study. It is well suited for learners and developers who want a hands-on YOLOv3 codebase in PyTorch. -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
...The project added multi-GPU training, seed settings for reproducible results, adaptive learning rate behavior based on batch size, and both step and cosine learning rate schedules. It also supports Adam and SGD optimizer choices, image cropping, adjustable parameters, and extensive code comments. It is a useful educational and applied repository for users who want to understand or customize YOLOv4 in PyTorch. -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch. -
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Jekyll theme: Adam Blog 2.0
The Minimum Viable Model website and Jekyll theme
Adam Blog 2.0 is a Jekyll theme that was built to be 100% compatible with GitHub Pages. If you are unfamiliar with GitHub Pages, you can check out their documentation for more information. Jonathan McGlone's guide on creating and hosting a personal site on GitHub is also a good resource. Jekyll is a simple, blog-aware, static site generator for personal, project, or organization sites. -
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Higher
higher is a pytorch library
...The library introduces utilities that convert standard torch.nn.Module instances into “stateless” functional forms, so parameter updates can be treated as differentiable operations. It also provides differentiable implementations of common optimizers like SGD and Adam, making it possible to backpropagate through an arbitrary number of inner-loop optimization steps. By offering a clear and flexible interface, higher simplifies building complex learning algorithms that require gradient tracking across multiple update levels. Its design ensures compatibility with existing PyTorch models. -
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SINGA
A distributed deep learning platform
...SINGA supports data parallel training across multiple GPUs (on a single node or across different nodes). SINGA supports various popular optimizers including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad, etc. SINGA records the computation graph and applies the backward propagation automatically after forward propagation. The optimization of memory are implemented in the Device class. SINGA supports loading ONNX format models and saving models defined using SINGA APIs into ONNX format, which enables AI developers to use models across different libraries and tools. ... -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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Smart Dataset-XML Viewer (outdated)
Smart viewer for the CDISC Dataset-XML Standard
This the old page for the "Smart Dataset-XML Viewer". It is a Java-based viewer for CDISC Submission files (SDTM, SEND, ADaM) in the new Dataset-XML Format. The Project has been renamed to "Smart Submission Dataset Viewer", and can be found at: https://sourceforge.net/projects/smart-submission-dataset-viewe/ -
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Learning to Learn in TensorFlow
Learning to Learn in TensorFlow
Learning to Learn, created by Google DeepMind, is an experimental framework that implements meta-learning—training neural networks to learn optimization strategies themselves rather than relying on manually designed algorithms like Adam or SGD. The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a meta-optimizer model that learns by observing and adapting to the optimization trajectories of other models. ... -
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PBSuite
Software for Long-Read Sequencing Data from PacBio
This currently hosts two projects created and maintained by Adam English. PBJelly - the genome upgrading tool. PBHoney - the structural variation discovery tool Both are contained within the PBSuite code found in downloads. ----- PBJelly ----- Read The Paper http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768 PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. ... -
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...Docelowo system ma zajmować się zarządzaniem plikami użytkownikami bazami danych serwerem pocztowym itp. Zapraszam wszystkich chętnych do wzięcia udziału w projekcie. Pozdrawiam Adam Bartoszek :).
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VoltMR
Pure java NGS mapping soft run on Hadoop 2.0
...Using 100 core, VoltMR finish typical exome sample (10GB),mapping, sort, mark duplicate, local realignment in 30 minitue. It use about 10GB to 15GB RAM for each hadoop mapper and reducer. Currently, VoltMR take fastq as a input and output bam/ADAM format. For DNA mapping, GATK compatible realignment/recalbration followed after mapping. For RNA mapping, splice aware algorithm is implemented. Volt is open source, released as "LGPLv3" -
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Adam
Adam - information management platform
Adam is opensource, cross-platform, mobile, extensible information management platform designed for unified storage, next-generation semantic retrial and processing of different types of documents. It has innovative, friendly and comfortable user interface for document viewing, editing and organizing. Adam can be used: - For creating unified personal information pool -
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rtcread-ds
A DS port of an RTC reader for GBA carts.
A DS port of an RTC reader for GBA carts. Program allows you to view the RTC data of the cart inserted in slot-2 of the DS, as well as edit the value of the RTC as desired. Original project created by Adam of Furlock's Forest (http://furlocks-forest.net/). -
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Gekko Timeseries Software
Timeseries handling, and solving of large-scale economic models
Gekko Timeseries Software is a free time-series oriented software package for timeseries handling, and solving and analyzing large-scale economic models. Since 2009, Gekko is being used by Danish ministeries, banks, interest groups and universities, for the simulation of economic and energy-related models. The software runs under Windows (.NET), and is open source (GNU GPL)
