Search Results for "can" - Page 12
Sort By:
Showing 549 open source projects for "can"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
1
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. -
2
Chess.jl
Julia chess programming library
A Julia chess programming library. This package contains various utilities for computer chess programming. There are functions for creating and manipulating chess games, chess positions and sets of squares on the board, for reading and writing chess games in the popular PGN format (including support for comments and variations), for creating opening trees, and for interacting with UCI chess engines. The library was designed for the purpose of doing machine learning experiments in computer... -
3
ReplMaker.jl
Simple API for building repl modes in Julia
...Suppose you've invented some language called MyLang and you've implemented a parser that turns MyLang code into Julia code which is then supposed to be executed by the Julia runtime. With ReplMaker.jl, you can simply hook your parser into the package and ReplMaker will then create a REPL mode where end users just type MyLang code and have it executed automatically. My hope is for this to be useful to someone who implements a full language or DSL in Julia that uses syntax not supported by Julia's parser and doesn't want to deal with the headache of making their own REPL mode. -
4
Learn Julia the Hard Way
Learn Julia the hard way
The Julia base package is pretty big, although at the same time, there are lots of other packages around to expand it with. The result is that on the whole, it is impossible to give a thorough overview of all that Julia can do in just a few brief exercises. Therefore, I had to adopt a little 'bias', or 'slant' if you please, in deciding what to focus on and what to ignore. Julia is a technical computing language, although it does have the capabilities of any general-purpose language and you'd be hard-pressed to find tasks it's completely unsuitable for (although that does not mean it's the best or easiest choice for any of them). ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
5
ApplicationBuilder.jl
Compile, bundle, and release julia software
Turn your Julia program into a standalone, distributable, statically-compiled "App". ApplicationBuilder compiles a Julia program and bundles it up into a distributable application, on macOS, Windows and Linux! After building, your users can download your application and run it without having Julia installed. -
6
VIKAMINE is a flexible environment for visual analytics, data mining and business intelligence - implemented in pure Java. It features several powerful visualization and mining methods, and can utilize background knowledge.
-
7
pycoQC
pycoQC computes metrics and generates Interactive QC plots
PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data. PycoQC relies on the sequencing_summary.txt file generated by Albacore and Guppy, but if needed it can also generate a summary file from basecalled fast5 files. The package supports 1D and 1D2 runs generated with Minion, Gridion and Promethion devices and basecalled with Albacore 1.2.1+ or Guppy 2.1.3+. PycoQC is written in pure Python3. Python 2 is not supported. -
8
libPGF
libPGF is an implementation of the Progressive Graphics File (PGF)
The Progressive Graphics File (PGF) is an efficient image file format, that is based on a fast, discrete wavelet transform with progressive coding features. PGF can be used for lossless and lossy compression. It's most suitable for natural images. PGF can be used as a very efficient and fast replacement of JPEG 2000. -
9
Luminance HDR
Complete solution for HDR photography
...Its graphical user interface, based on Qt5, runs on a variety of platforms, such as Microsoft Windows, Mac OS X 10.9 and later and several Unix flavors (Linux, FreeBSD and others). Input images can be supplied in multiple formats, from JPEG to RAW files. In the same way, output can be saved in many different formats as well, from JPEG to TIFF (both 8 bit and 16 bit per channel), enabling all the power of your post processing tools. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
10
OpenFrames
Real-time interactive 3D graphics API for scientific simulations
...Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently used by three NASA programs: Copernicus (NASA JSC), the General Mission Analysis Tool (GMAT, NASA GSFC), and a Virtual Reality exploration tool (NASA GSFC). -
11
Davinci
Davinci is a DVsaaS (Data Visualization as a Service) Platform
...It aims to provide a one-stop data visualization solution, which could be both independently used as a public cloud/private cloud and integrated into third-party systems as plugin. A simple configuration on Davinci UI can meet multiple visualization requirements. It also supports other visualization features like advanced interaction, industry analysis, pattern searching, social intelligence, etc. Sharing and intelligence capability means users could share their dashboards with others, which stimulates them to improve the visualization ability both in aesthetic perception and technical skills. ... -
12
ElectronDisplay.jl
An Electron.jl based figure and table display.
This package provides a display for figures, plots and tables. When you load the package, it will push a new display onto the Julia display stack and from then on it will display any value that can be rendered as png, svg, vega, vega-lite or plotly in an electron-based window. This is especially handy when one works on the REPL and wants plots or tables to show up in a nice window. -
13
ArrayFire.jl
Julia wrapper for the ArrayFire library
...ArrayFire.jl wraps the ArrayFire library for Julia, and provides a Julia interface. Install ArrayFire library: either download a binary from the official site, or you can build from source. -
14
Jupytab
Display in Tableau data from Jupyter notebooks
Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab. -
15
OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
...See the installation manual or "OzGIS Installation" Youtube video for help with getting started. I am unable to show OzGIS to you, so suggest that you search for "OzGIS lloyd" on Youtube for demonstration videos or "OzGIS" on Pinterest for example maps. You can mail me at cleverco@users.sourceforge.net or use the Discussion tab or post a ticket for problems. -
16
CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
...Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. Let’s break down a CNN into its basic building blocks. A tensor can be thought of as an n-dimensional matrix. In the CNN above, tensors will be 3-dimensional with the exception of the output layer. A neuron can be thought of as a function that takes in multiple inputs and yields a single output. The outputs of neurons are represented above as the red → blue activation maps. -
17
JuliaDB.jl
Parallel analytical database in pure Julia
JuliaDB is a package for working with large persistent data set. JuliaDB provides distributed table and array datastructures with convenient functions to load data from CSV. JuliaDB is Julia all the way down. This means queries can be composed with Julia code that may use a vast ecosystem of packages. -
18
ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
19
repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag... -
20
CUDAnative.jl
Julia support for native CUDA programming
...It is built on the CUDA toolkit and aims to be as full-featured and offer the same performance as CUDA C. The toolchain is mature, has been under development since 2014, and can easily be installed on any current version of Julia using the integrated package manager. -
21
StellarGraph
Machine Learning on Graphs
...The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. ... -
22
CuArrays.jl
A Curious Cumulation of CUDA Cuisine
CuArrays provides a fully-functional GPU array, which can give significant speedups over normal arrays without code changes. CuArrays are implemented fully in Julia, making the implementation elegant and extremely generic. -
23
Cubature.jl
One- and multi-dimensional adaptive integration routines for Julia
...The Cubature module implements two schemes for this adaptation: h-adaptivity (routines hquadrature, hcubature, hquadrature_v, and hcubature_v) and p-adaptivity (routines pquadrature, pcubature, pquadrature_v, and pcubature_v). The h- and p-adaptive routines accept the same parameters, so you can use them interchangeably, but they have very different convergence characteristics. -
24
tikzcd-editor
A simple visual editor for creating commutative diagrams
A simple visual editor for creating commutative diagrams. -
25
graphdot
Visualize Go module dependencies in Graphviz DOT format
Visualize Go module dependencies in Graphviz DOT format. Run graphdot in the directory of any project using Go modules with a go.mod file to print out a dependency graph in Graphviz DOT format. The output can be piped directly into dot to generate a PNG image file. For large graphs with many nodes of dependencies, you may want to generate an SVG file to allow you to zoom in with high fidelity and save disk space instead. If you like a more UML'ish style, you can use the provided graph properties from uml.gprops.