Based on our record, GitHub Desktop should be more popular than Scikit-learn. It has been mentiond 131 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.
1.Download the github desktop. 2.Open the first contribution repository. 3.Open the github app and clone the repository. - Source: dev.to / 16 days ago
This is a simple yet powerful GUI for Git that integrate well with GitHub. It’s available for Windows and macOS. You can download it from the GitHub Desktop website: https://desktop.github.com/. - Source: dev.to / about 1 month ago
Congrats on the launch! It's always exciting to see more competition in the version control space. One question I have is whether you guys are better than: https://desktop.github.com/ This seems to do the exact same thing, be free forever, and have a more mature GUI that is also easier to use than regular terminal git. In my firm, even with people who don't know how to code, they can use github desktop (since it... - Source: Hacker News / 5 months ago
- Product designers for open-source hardware. Various design files, SVG etc. I’ve experimented with a “GUI only” git flow - just to see what is possible, so I could introduce the concept to others. I found GitHub desktop app (https://desktop.github.com/)did a great job of visually showing git flows and functions, but for a non-tech/programmming person, the tool would be daunting. Curiosity what your suggested tech... - Source: Hacker News / 7 months ago
Just use github desktop its an open source tool https://desktop.github.com/. Source: 7 months 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 / 20 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
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