I am working on a project which consists in detecting epileptic seizures for patients from the EEG signal for this I developed a web application using spring boot, mysql and react js, and I built my classification model machine leraning with Jupyter using the scikit-learn library.
My problem is how can I integrate this model in my application so that a notification will be sent to the user when the patient suffers a epileptic seizure .
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I am using a teachable machine to do my wake word recognition, which runs in electron. Now the model works fine, but I want to visualize it. I have seen tutorials on how to visualize TensorFlow ,Keras models etc.. But what to do for a teachable machine model.
I have seen various methods of deploying machine learning models on the cloud, but I just wanted to know if we can create a program that uses machine learning not from the cloud but instead uses the model trained on the same computer. What I mean is can I create a simple Tic-Tac-Toe game where the computer uses machine learning to play against the human player, with both the game file and the model residing on the same computer, one communicating with the other?
Yep! You can. It’s called reinforcement learning. There are some pretty good tutorials about it here:
https://github.com/simoninithomas/Deep_reinforcement_learning_Course
I'm developing a cross-platform app (iOS/Android/web) and am loving the fast, cheap on-device image labeling feature of ML Kit on mobile. Is there a way to replicate the behavior on the web? Are the ML Kit models available for re-use with a different ML library so it can be repurposed?
Unfortunately, it does not seem like ML Kit allows you to export models created using it, only import models. However, tensorflow.js lets you run TensorFlow models on the web. If you are looking for an easy way to create models there are several web-based programs which allow you to easily create ML models and export as TensorFlow Lite (which can be run in tensorflow.js or even hosted on Firebase). A couple I have heard of are: lobe.ai and ml5.js. Hope this helps.
How a machine learning algorithm(Present in Spark MLlib) can be applied to Data collected from sensors in KAA. I haven't found any such use case built on KAA. My requirement is to collect the live streams of data, processing and cleaning the same and applying a machine leaning algorithm in KAA.
I have done this by collecting the data using Apache nifi and through Kafka passing the data to Spark Streaming Application on which I am applying the machine learning algorithm.
I want to perform the same in KAA as an IoT platform.
I'm working on a project where I train a text classifier and I need to create a web app to let the user enter text for classification. Currently all the code is written in Python and I'm using scikit-learn library. I've encountered a problem installing the scikit-learn on heroku, in order for my Python code to run on the server. I don't mind changing everything (Python language, Flask web framework, scikit learning library, heroku web-app hosting services), I just need to get this thing to work :)
Do any one of you in CV community had any experience in making a web-app that uses a learning library online? The web app hosting should be a free one though, as this project is not commercial, and also it would be very nice to have Python behind the scenes.
N.B. The classifiers that should be supported by the library are multiclass svm and naive bayes.
How about trying google app engine? It has python (2.5 and 2.7) and can be free.