Keras
TensorFlow
PyTorch
Scikit-learn
OpenCV
TFlearn
Clarifai
Microsoft Cognitive Toolkit (Formerly CNTK)
Teachable Machine
Google Cloud Machine Learning
Amazon Machine Learning
OpenCV
MLJAR
ML5.js
Scikit-learn
TensorFlow
Teachable MachineBased on our record, Teachable Machine should be more popular than Keras. It has been mentiond 55 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.
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 3 days ago
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 months ago
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / about 2 months ago
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
Not sure if I've seen anything of the sort, seems rather specific. Maybe try a Teachable Machine project? https://teachablemachine.withgoogle.com/. - Source: Hacker News / 2 months ago
Train a computer to recognize your images, sounds, and poses. Use this resource to gain a better understanding. - Source: dev.to / 6 months ago
We will create an machine learning model that can classify Arabic and English books. To collect, train, and test data, we will use Teachable Machine from Google. - Source: dev.to / 10 months ago
a lot of places! But for a high schooler, better to focus at what you want to do first. Or if you still haven't gotten any idea, try a simple explanation on what ml is without the math on youtube and tinker around a no code machine learning platform like https://teachablemachine.withgoogle.com/. Source: about 1 year ago
The principle is roughly the same as it is possible with teachablemachine.withgoogle.com. Source: about 1 year ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Google Cloud Machine Learning - Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Amazon Machine Learning - Machine learning made easy for developers of any skill level
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
OpenCV - OpenCV is the world's biggest computer vision library
