Based on our record, Scikit-learn should be more popular than Particle.io. It has been mentiond 31 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.
Look into AWS Greengrass, Robomaker, etc. If you're looking for more customization. Or you could use an all-in-one product like from particle.io if you'd more of an out-of-the-box solution. Source: about 2 years ago
5) look at using a GPRS or LTE (look at particle.io) cell monitor a fridge or freezer. Source: over 3 years ago
I really dig your KYC reports. Please do Particl particle.io next :). Source: over 3 years ago
That's not how I read the OP's proposal. It sounds more like they want to build something like the service that http://particle.io/ appears to provide. Source: almost 4 years ago
Looks cool! How does this differ from http://particle.io ? - Source: Hacker News / almost 4 years ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 6 months ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 12 months 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 / over 1 year 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 2 years ago
AWS IoT - Easily and securely connect devices to the cloud.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
AWS Greengrass - Local compute, messaging, data caching, and synch capabilities for connected devices
OpenCV - OpenCV is the world's biggest computer vision library
ThingSpeak - Open source data platform for the Internet of Things. ThingSpeak Features
NumPy - NumPy is the fundamental package for scientific computing with Python