GameMaker Studio might be a bit more popular than Scikit-learn. We know about 36 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.
I am no game developer but have over the past few years played around with GameMaker and their studio software[0]. I would imagine it to be one of the easiest ways to get started with making a 2D game. Then there is also the option of not jumping directly into the coding bit, and rather cultivate in your son the ability to do on paper designs first. This is a skill that would probably benefit him later in life as... - Source: Hacker News / 5 months ago
My introduction to programming was when I was 10 with GameMaker. I found that the same company has a product with the same name that seems to be the spiritual succesor of it[0]. I allowed me to start with very simple no-code and move on to incrementaly add codes nipets here and there. Eventually I went crazy and tried to make a game fully with code, avoiding all the tools the engine gave me, just as an experiment... - Source: Hacker News / 5 months ago
If you're looking for a tool that's fairly simple for a beginner, but has the flexibility to also offer more advanced features as you learns more, and has plenty of tutorials and learning resources available for a novice programmer starting out: it's worth noting that GameMaker has recently (i.e. 2 weeks ago) been made completely free for non-commercial users. Source: 6 months ago
Go to https://gamemaker.io/en, and accept the new TOS. You won't be able to log in through the software until you do. Source: 7 months ago
There are a thousand ways to get started. I'm assuming you have no programming experience, in which case I'd start with an all in one package, like: Https://gamemaker.io/en. Source: 9 months 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 / almost 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
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
Godot Engine - Feature-packed 2D and 3D open source game engine.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Unity - The multiplatform game creation tools for everyone.
OpenCV - OpenCV is the world's biggest computer vision library
GDevelop - GDevelop is an open-source game making software designed to be used by everyone.
NumPy - NumPy is the fundamental package for scientific computing with Python