Balsamiq might be a bit more popular than Scikit-learn. We know about 30 links to it since March 2021 and only 28 links to Scikit-learn. 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.
A few apps that are a joy to use: https://ia.net/writer for writing. https://usecontrast.com/ for checking contrast. https://sipapp.io/ for picking colors. https://nova.app/ for editing code. https://cleanshot.com/ for screenshots. https://getpixelsnap.com/ for measuring elements on screen. https://netnewswire.com/ for reading things via RSS. https://panic.com/transmit/ for file transfers. https://usefathom.com/... - Source: Hacker News / 6 months ago
I think the best practical approach for designing UIs is to download (and buy) Balsamic[0] and use that to design UIs. Cut through the nonsense of colours and pixels in the first instance and just lay things out logically and simply. [0] https://balsamiq.com. - Source: Hacker News / 6 months ago
Create a low-fidelity mockup or wireframe of your MVP using tools like Balsamiq, Sketch, or Figma. Or use an easier-to-use tool like Uizard, which also has text-to-design capabilities. Source: 10 months ago
Just for drawing mock app screens, I have found Balsamiq[0] to be pretty good (you can do a bunch of stuff with the trial version itself). Not affiliated with them in any way. [0]: https://balsamiq.com/. - Source: Hacker News / 11 months ago
Balsamiq has been pretty good for me so far. It's super bare-bones so it's better for copy mockups than actual UX design. It's also a lot easier than Figma. Note that you don't have to use the default comic sans, but I do because it's funny. Source: over 1 year 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 / 3 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 / 12 months 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
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: over 1 year ago
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