AWS IoT Core VS Scikit-learn

AWS IoT Core Reviews

Scikit-learn Reviews

AWS IoT Core mentions (8)

• WebSockets, gRPC, MQTT, and SSE - Which Real-Time Notification Method Is For You?

  MQTT - AWS IoT Core offers a managed MQTT message broker, giving you easy access to your devices. Fun fact, this is what powers the notifications in Serverlesspresso. - Source: dev.to / 7 months ago

• Serverless Facial Recognition Voting Application Using AWS Services

  AWS IoT: For real-time communication between the server and the frontend application. - Source: dev.to / about 1 year ago

• Building Serverlesspresso

  AWS IoT Core is a service that allows you to connect your devices securely to the AWS cloud and with ease. Option for device management, data processing as well as integration with other AWS services is provided. Click here for more on AWS IoT Core. - Source: dev.to / about 1 year ago

• Use EventBridge to handle API requests

  From here you can do all sorts of actions. For example, the serverless-coffee project used IOT Core. With IOT Core you can notify the end-user with status updates. And notify the barista that what kind of coffee needs to be created. - Source: dev.to / about 1 year ago

• API Gateway Websockets vs IoT Core

  When you need websockets in a project on AWS most likely API Gateway Websockets (I will refer to it as API Gateway from now on) is the first service coming to mind. At some point when looking into options, I ran into IoT Core instead. I thought this was meant only for very specific scenarios involving hardware; however it also supports MQTT over websockets which makes it an amazing choice for web and app. I think... - Source: dev.to / over 1 year ago

Scikit-learn mentions (28)

• How to Build a Logistic Regression Model: A Spam-filter Tutorial

  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 / 3 months ago

• Link Prediction With node2vec in Physics Collaboration Network

  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 / 11 months ago

• WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point

  The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: about 1 year ago

• Help on using R for Machine Learning?

  Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago