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Thingsboard might be a bit more popular than machine-learning in Python. We know about 9 links to it since March 2021 and only 7 links to machine-learning in Python. 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.
You might find something more attuned to that use case to be more helpful out of the box (like thingsboard.io) but if you're committed to django, set up an API endpoint to receive json updates ('events') sent from the arduino. Source: about 1 year ago
Introduction:As a 100% open source IoT platform that can be hosted as a SaaS or PaaS solution, Thingsboard can provide device management, data collection, processing and visualization for your IoT project. The standard protocols that provide device connectivity such as MQTT, CoAP, and HTTP are all available on ThingsBoard. In addition, it supports cloud and local deployment and provides more than 30 customizable... Source: over 1 year ago
Then host a ThingsBoard server and use the HTTP API to push data from the device. You can send alerts with Pushover. Source: over 1 year ago
**Source** [thingsboard (a foreign iot platform)](https://thingsboard.io/). Source: over 1 year ago
ThingsBoard is an open-source IoT platform for data collection, processing, visualization and device management. It supports device connectivity via protocols, such as MQTT, CoAP and HTTP, and supports both cloud and private deployments. Deliver, monitor and control your IoT entities in a secure way using rich server-side APIs that define the relationships between your devices, assets, customers, or any other... - Source: dev.to / over 1 year ago
After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 1 year ago
Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 1 year ago
MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 2 years ago
Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ioBroker - flexible and modular application for the IoT and Smarthome
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
Home-Assistant.io - Home Assistant is an open-source home automation platform running on Python 3.
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.