Search Results for "hard"
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Showing 14 open source projects for "hard"
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1
Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy). ... -
2
Personal Management System
Your web application for managing personal data
It's easier to understand this web application when you think about a CMS (WordPress) or CRM (SugarCRM); the logic behind this system is very similar to those two. My PMS may offer fewer possibilities than those systems above, but it just does what I want it to do. Additionally, writing extensions is not too hard, depending on the logic required. Anyone with development knowledge can pretty much write their own extensions for personal needs. Keep a track of your personal goals. You can use tools to keep track of your goals progress or use the payments submodule to keep an eye of the money amount that you want to collect for something. Add any personal note to the desired category. ... -
3
FunSQL.jl
Julia library for compositional construction of SQL queries
FunSQL is a Julia library for the compositional construction of SQL queries. Julia programmers sometimes need to interrogate data with the Structured Query Language (SQL). But SQL is notoriously hard to write in a modular fashion. FunSQL exposes full expressive power of SQL with compositional semantics. FunSQL allows you to build queries incrementally from small independent fragments. This approach is particularly useful for building applications that programmatically construct SQL queries. -
4
JDF.jl
Julia DataFrames serialization format
...Collectively, the column files, the metadata file, and the folder is called a JDF "file". JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. E.g. Python's numpy arrays are C objects, but all the vector types used in JDF are Julia data types. -
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5
CleanVision
Automatically find issues in image datasets
...CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. CleanVision helps you automatically identify common types of data issues lurking in image datasets. This package currently detects issues in the raw images themselves, making it a useful tool for any computer vision task such as: classification, segmentation, object detection, pose estimation, keypoint detection, generative modeling, etc. -
6
IoTDB
Apache IoTDB
Apache IoTDB (Database for Internet of Things) is an IoT native database with high performance for data management and analysis, deployable on the edge and the cloud. Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. In the scene of factories, there... -
7
data-diff
Efficiently diff rows across two different databases
...Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across hundreds of tables, with low latency and at a reasonable infrastructure cost is a hard problem, and most data teams we’ve talked to, have faced data quality issues in their replication processes. The hard truth is that the quality of the replication is the quality of the data. Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates. -
8
Learn Julia the Hard Way
Learn Julia the hard way
...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). Julia was developed with the occasional reference to R, and with an avowed intent to improve upon R's clunkiness. R is a great language, but relatively slow, to the point that most people use it to rapidly prototype, and then implement the algorithm for production in Python or Java. ... -
9
Kale
Kubeflow’s superfood for Data Scientists
...The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. Additionally, data science often involve processes of data exploration, iterative modelling and interactive environments (mostly Jupyter notebook). -
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10
iCubing
Several OLAP algorithms, data structures and HPC OLAP versions
...There are also several cube types, i.e. alphanumeric cubes, text cubes with unstructured data and geo cube with geo types, dimensions, measures and hierarchies, so the OLAP area continues a hard challenge after more than 20 years of the seminal paper of Jim Gray et al. in 1997. Our team has more than 15 years of experience in developing OLAP kernels. -
11
New CTruck3D Rally
Free-roaming 3D racing game featuring advanced terrain rendering
...Written in C++, featuring multithreading (2 threads): a total remake of the first 3D game I did years ago, CTruck3D_Simplex and sequels. This works better, thought the basic idea is the seme. Similar to the old games Terep2 and "1nsane". I am an algorithmist, not a game developer: so it was hard for me to put this togather. But I did this tribute to videogames. Have lots of fun! KEYS: mouse: primary camera control arrows: drive vehicle ; SHIFT: turbo ; TAB: change car. o: change camera ; 1,2: zoom-in/out ; 3,4 : horizontal and vertical camera placement (internal view) u: respawn car c,v,f,r :secondary camera control. 8,9:plane drv -
12
JChart2D
jchart2d is a real-time charting library written in java.
JChart2D is a easy to use component for displaying two- dimensional traces in a coordinate system written in Java. It supports real-time (animated) charting, custom trace rendering, Multithreading, viewports, automatic scaling and labels. Former UI controls (right click context menu, file menu) have been ported to the subproject jchart2d-uimenu (https://sourceforge.net/projects/jchart2d-uimenu.jchart2d.p/) for the benefit of having no dependencies to 3rd party libraries. -
13
iOVFDT
iOVFDT algorithm of incremental decision tree
...Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference. When processing big data, it is hard to implement pre-processing and sampling in full batches. To solve this trade-off, we propose a new decision tree so called incrementally optimized very fast decision tree (iOVFDT). Inheriting the use of Hoeffding bound in VFDT algorithm for node-splitting check, it contains four optional strategies of functional tree leaf, which improve the classifying accuracy. ... -
14
ADrillForce project is now part (a component) of the larger project forssim. This project will close. ADrillForce is a reference implementation of haptic (force feedback) algorithms for virutal hard material collision handling and data modification.
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