LicenseSpring
Quick License Manager
Labs64 NetLicensing
10Duke Enterprise
Keygen
Open iT LicenseAnalyzer
VIZOR
wyDay LimeLM
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
htm.java
Issuing and managing software licenses does not have to be difficult. LicenseSpring allows software vendors to control the state of their application according to their license agreements. It's easy to configure the simplest or the most complex license policies, and then use them as a template when issuing licenses.
Connections from the Software Vendor's client applications to our cloud based service is done through one of our SDKs or through the use of our RESTful APIs.
We also provide an end-user portal as well as a distributor portal to allow self-serve support, as well as aide in providing a mechanism to help vendors distribute their software through resellers.
LicenseSpring Scikit-learnNo features have been listed yet.
LicenseSpring's answer
We are a spin-off of PDF Pro Software Inc, a company that develops and commercializes PDF Editing software for desktop. Back in 2017, we were looking for a good, no-nonsense license manager on the market, and to our surprise we found two types of solutions: the first category were archaic but expensive incumbents such as Flexera or Thales who were not interested in creating modern user-friendly Licensing solutions. The other category were many startups, whom we did not trust to survive in the long run, and simply did not have the capabilities we needed. We decided to build our own licensing tool, and offer it initially for free to anyone who wanted to give us feedback. Today we boast over 1000 active accounts with vendors of all sizes and industries. Our goal is to be the best licensing API in the world.
LicenseSpring's answer
I think our ease of use, and our no nonsense approach to our customer support / client onboarding.
LicenseSpring's answer
Do not chose Licensespring if you would like to be price gouged by Flexera or Thales, as we are an order of magnitude cheaper since we charge based on usage, not based on licensed revenue.
Based on our record, Scikit-learn should be more popular than LicenseSpring. It has been mentiond 29 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
User licenses (these are either machine based, or named user based, like having a unique user name). You'll need to build some type of license entitlement functionaly on your software, or integrate it with something like LicenseSpring. Source: about 1 year ago
If I were concerned about licensing, then I'm really not sure I'd put my faith into a library like thus - not least that if the app just shipped with the dll, then it could be swapped out in the blink of an eye with a stub. There's significantly more involved in managing this sort of thing that a simplistic library such as this can manage. Companies concerned with licensing usually do it because they're protecting... - Source: Hacker News / over 1 year ago
Hello, you can also try us out (licensespring.com), we're similar to the providers you mentioned. Source: almost 2 years ago
I found https://licensespring.com/ which sounds amazing but it seems once you apply it the code is still held locally even if the licence is not O.K., meaning it can still be reverse engineered. Source: almost 2 years ago
Take a look, might be suitable: https://licensespring.com/. Source: almost 2 years ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 16 days ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 4 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / about 1 year ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago
Quick License Manager - Quick License Manager (QLM) is a license protection framework that creates professional and secure license keys to protect software against piracy.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Labs64 NetLicensing - Monetize your digital products and services
OpenCV - OpenCV is the world's biggest computer vision library
10Duke Enterprise - Powerful cloud-based licensing solution designed for fast-growing software businesses looking to scale up software licensing & minimize friction.
NumPy - NumPy is the fundamental package for scientific computing with Python