Learn more about using the SensiML software, edge AI analytics, embedded sensors, and other smart IoT sensing topics from this growing collection of videos.
Upcoming Live Tutorials
| Date | Time | Topic | Presenter(s) |
|---|
Nothing currently scheduled. Please check back regularly for updates.
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Tutorials
- Microchip Design Week 2022What’s New in Machine Learning at the EdgeMicrochip and SensiML discuss design trends and the key benefits for designing for IoT edge applications.
- "How to Create Edge AI Models for Industrial Sensor Nodes"An onsemi and SensiML Webinar: 12/09/2021During this webinar, learn how onsemi and SensiML have collaborated to deliver a complete machine learning solution for industrial applications.
- SensiML-QORC Tech Topics SeriesSession 1 - Jan 27, 2021Connecting New I2C Sensors to QuickFeather and Capturing the Data in SensiML For Further Learning...
- SensiML-QORC Tech Topics SeriesSession 2 - Feb 3, 2021Incorporating TensorFlow Lite NN Into Your SensiML Machine Learning Algorithm For Further Learning...
- SensiML-QORC Tech Topics SeriesSession 3 - Feb 24, 2021Programming QuickFeather's FPGA Using SymbiFlow For Further Learning...
- SensiML-QORC Tech Topics SeriesSession 4 - Mar 3, 2021Connecting QuickFeather and Data Capture Lab over WiFi Using the ESP32 For Further Learning...
- SensiML-QORC Tech Topics SeriesSession 5 - Mar 10, 2021QuickFeather FPGA + MCU Application Examples
- SensiML-QORC Tech Topics SeriesSession 6 - Mar 17, 2021ML101 – A Survey of ML Classifier Types and Their Use
- SensiML-QORC Tech Topics SeriesSession 7 - Apr 7, 2021Working with Audio Data using QuickFeather and SensiML
- SensiML-QORC Tech Topics SeriesSession 8 - Apr 21, 2021SensiML Model Tuning - Improving Baseline Results Beyond AutoML Defaults
- TinyMLBoxing Demo Using ArduinoDemonstrate how to collect and annotate a high-quality dataset of boxing gestures using the SensiML Analytics Toolkit and Arduino Nano 33 BLE Sense For Further Learning...
- SensiML Tutorial SeriesChapter 1 - Introduction to SensiML Analytics ToolkitThe goal of this guide is to provide a step-by-step tutorial on how to use the SensiML Toolkit. We will walk through a 'Hello World'-style project for sensor applications. For Further Learning...
- SensiML Tutorial SeriesChapter 2 - Fundamentals of Model BuildingBefore you build an application, it is important to create a data collection plan. For Further Learning...
- SensiML Tutorial SeriesChapter 3 - Quick Start ProjectsThis project showcases the continuous event type described previously in Data Collection Planning. For Further Learning...
- SensiML Tutorial SeriesChapter 4 - Getting Started with Data Capture LabThe first step of creating a sensor application is going to be collecting and labeling raw sensor data into events of interest through the Data Capture Lab (DCL). For Further Learning...
- SensiML Tutorial SeriesChapter 5 - Capturing Event Sensor DataNow it’s time to collect some examples of the event you are trying to detect. For Further Learning...
- SensiML Tutorial SeriesChapter 6 - Labeling Your DataOnce you have collected examples of the events you are trying to detect, it’s now time to label those events. For Further Learning...
- SensiML Tutorial SeriesChapter 7 - Getting Started with Analytics StudioThe Analytics Studio uses AutoML to abstract the complexities of machine learning algorithms and translates them into a user-friendly interface. For Further Learning...
- SensiML Tutorial SeriesChapter 8 - Building a Model with SensiML DashboardThe Model Building part of the Analytics Studio uses SensiML’s AutoML to build a model that gives you control of the features you want in your device. For Further Learning...
- SensiML Tutorial SeriesChapter 9 - Validating Your ResultsThe final step after creating a model is to validate your Knowledge Pack running on your edge device through the SensiML TestApp. For Further Learning...
- SensiML Tutorial SeriesChapter 10 - Advanced Model BuildingFor data scientists, we recommend working within Analytics Studio Notebook. You can specify the advanced features, transforms, training algorithm, and validation methods that go into your model. For Further Learning...
Microchip Design Week 2022
What’s New in Machine Learning at the Edge
Microchip and SensiML discuss design trends and the key benefits for designing for IoT edge applications.
"How to Create Edge AI Models for Industrial Sensor Nodes"
An onsemi and SensiML Webinar: 12/09/2021
During this webinar, learn how onsemi and SensiML have collaborated to deliver a complete machine learning solution for industrial applications.
SensiML-QORC Tech Topics Series
Session 1 - Jan 27, 2021
Connecting New I2C Sensors to QuickFeather and Capturing the Data in SensiML For Further Learning...
SensiML-QORC Tech Topics Series
Session 2 - Feb 3, 2021
Incorporating TensorFlow Lite NN Into Your SensiML Machine Learning Algorithm For Further Learning...
SensiML-QORC Tech Topics Series
Session 3 - Feb 24, 2021
Programming QuickFeather's FPGA Using SymbiFlow For Further Learning...
SensiML-QORC Tech Topics Series
Session 4 - Mar 3, 2021
Connecting QuickFeather and Data Capture Lab over WiFi Using the ESP32 For Further Learning...
SensiML-QORC Tech Topics Series
Session 5 - Mar 10, 2021
QuickFeather FPGA + MCU Application Examples
SensiML-QORC Tech Topics Series
Session 6 - Mar 17, 2021
ML101 – A Survey of ML Classifier Types
and Their Use
SensiML-QORC Tech Topics Series
Session 7 - Apr 7, 2021
Working with Audio Data using QuickFeather and SensiML
SensiML-QORC Tech Topics Series
Session 8 - Apr 21, 2021
SensiML Model Tuning - Improving Baseline Results Beyond AutoML Defaults
TinyML
Boxing Demo Using Arduino
Demonstrate how to collect and annotate a high-quality dataset of boxing gestures using the SensiML Analytics Toolkit and Arduino Nano 33 BLE Sense For Further Learning...
SensiML Tutorial Series
Chapter 1 - Introduction to SensiML Analytics Toolkit
The goal of this guide is to provide a step-by-step tutorial on how to use the SensiML Toolkit. We will walk through a 'Hello World'-style project for sensor applications. For Further Learning...
SensiML Tutorial Series
Chapter 2 - Fundamentals of Model Building
Before you build an application, it is important to create a data collection plan. For Further Learning...
SensiML Tutorial Series
Chapter 3 - Quick Start Projects
This project showcases the continuous event type described previously in Data Collection Planning. For Further Learning...
SensiML Tutorial Series
Chapter 4 - Getting Started with Data Capture Lab
The first step of creating a sensor application is going to be collecting and labeling raw sensor data into events of interest through the Data Capture Lab (DCL). For Further Learning...
SensiML Tutorial Series
Chapter 5 - Capturing Event Sensor Data
Now it’s time to collect some examples of the event you are trying to detect. For Further Learning...
SensiML Tutorial Series
Chapter 6 - Labeling Your Data
Once you have collected examples of the events you are trying to detect, it’s now time to label those events. For Further Learning...
SensiML Tutorial Series
Chapter 7 - Getting Started with Analytics Studio
The Analytics Studio uses AutoML to abstract the complexities of machine learning algorithms and translates them into a user-friendly interface. For Further Learning...
SensiML Tutorial Series
Chapter 8 - Building a Model with SensiML Dashboard
The Model Building part of the Analytics Studio uses SensiML’s AutoML to build a model that gives you control of the features you want in your device. For Further Learning...
SensiML Tutorial Series
Chapter 9 - Validating Your Results
The final step after creating a model is to validate your Knowledge Pack running on your edge device through the SensiML TestApp. For Further Learning...
SensiML Tutorial Series
Chapter 10 - Advanced Model Building
For data scientists, we recommend working within Analytics Studio Notebook. You can specify the advanced features, transforms, training algorithm, and validation methods that go into your model. For Further Learning...
