Keras
TensorFlow
PyTorch
Scikit-learn
TFlearn
OpenCV
Clarifai
DeepPy
MIT App Inventor
Thunkable
Kodular
Android Studio
Bubble.io
AppyBuilder
Xamarin.Android
IntelliJ IDEA
MIT App InventorMIT App Inventor might be a bit more popular than Keras. We know about 40 links to it since March 2021 and only 31 links to Keras. 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.
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 1 month 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 1 month 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 / 11 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
Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more. - Source: dev.to / over 1 year ago
First thought, play with MIT App Inventor https://appinventor.mit.edu/, they have dedicated blocks for graphing and cross-platform implementations of Bluetooth for Android and iOS. The data format is still up to you. Source: 12 months ago
Or you could go to https://appinventor.mit.edu/ and design your own custom app (no widget, though). Source: about 1 year ago
If you want to make a mobile app you could try https://appinventor.mit.edu/. Source: about 1 year ago
Maybe a raspberry pi that's on 24/7 connected to wifi and use that to send the wake over lan signal to the server? Arduino on the power pins also works, I did something quite similar but with a Bluetooth board, the code was really simple I just made an Android app with MIT app inventor that sent a signal to the hc_05 bt board, once the Arduino received that signal it shorted the power pin to 5v for half a second... Source: over 1 year ago
If your idea isn't complicated, have a look at MIT App Inventor. It literally is, drag-and-drop. That should get you started. Source: over 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.
Thunkable - Powerful but easy to use, drag-and-drop mobile app builder.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Kodular - Much more than a modern app creator without coding
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Android Studio - Android development environment based on IntelliJ IDEA