Based on our record, Scikit-learn should be more popular than Facebook AR Studio. It has been mentiond 28 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.
With the assistance of its parent company Meta, Instagram has just recently launched the beta of its AR ads through its Spark AR Platforms. This interactive ad layout allows users to interact with their ads whether it's trying on clothes or testing out furniture for a new home. Meta insists that these engaging ads will allow brands to “prepare for the metaverse,” as many are anticipating and developing technology... Source: over 1 year ago
I remember seeing this Corridor Crew video and they used something called Spark AR to do real-time face filters. Source: about 2 years ago
Like u/Nexen4 says, create the character in a modelling package, then import that into SparkAR to make a filter. Source: over 2 years ago
I haven't really used any. Though a friend of mine was playing with Spark AR Studio from Facebook. Source: over 2 years 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
Apple ARKit - A framework to create Augmented Reality experiences for iOS
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Snap Art - Snap's augmented reality platform
OpenCV - OpenCV is the world's biggest computer vision library
Shopify AR - Create AR experiences for your online store
NumPy - NumPy is the fundamental package for scientific computing with Python