The platform offers various deployment options, including exporting models to different formats that are optimized for specific edge devices. This flexibility ensures that your models can be efficiently utilized across your target hardware. Review collected by and hosted on G2.com.

The platform might feel somewhat limited in terms of building very complex or specialized models. Users with advanced machine learning needs might desire more extensive customization options or support for more advanced model architectures. Review collected by and hosted on G2.com.

The platform provides a range of data augmentation and preprocessing tools that help enhance the quality of your training data. These features can be particularly beneficial when dealing with limited datasets, as they contribute to better model performance and generalization. Review collected by and hosted on G2.com.

Although Edge Impulse provides a wealth of documentation and resources, some users might find it helpful to have offline documentation available for situations when they're working in environments with limited internet access. Review collected by and hosted on G2.com.

appreciate Edge Impulse for its user-friendly interface, machine learning capabilities tailored for edge devices, and its support for developing and deploying AI models for various applications Review collected by and hosted on G2.com.

There are some limitations in terms of certain advanced customization options, compatibility with specific hardware, or the learning curve for those who are new to machine learning and IoT technologies. Review collected by and hosted on G2.com.

I enjoy how easy it is to import and scale data. Overall, Edge Impulse is a platform. It could be simplified for everyday users and offer more options for diverse applications of knowledge. Review collected by and hosted on G2.com.

Whenever you retrain the model, there are changes in the calculated accuracy results. This makes it difficult to rely on Edge Impulse's classification accuracy consistently. Review collected by and hosted on G2.com.

The look and feel and the ease of use. I like the simple and logical way the workflow is organised. Review collected by and hosted on G2.com.

Minimal data import and data scaling abilities. One big problem I had was the time scaling, which is restricted to milliseconds - this is not helpful when importing data from many time series databases Review collected by and hosted on G2.com.

Edge impulse is one of the emerging platforms for embedded ML and is free for developers. Without specialised hardware like Arduino or raspberry pi, many real-time and time-consuming machine learning problems can be solved quickly. The best thing about this is you can use your mobile phone, computer or a supported development board. The data collection is super easy, and the dashboards help you manage your data. For example- you can view your previous data, projects and devices you used to connect etc. Very easy to use, just scan the QR code and the device gets connected via a link. Like any ML model, train and test data sets need to be created and you can create various labels for your reference. You can add filters to improve your results or for the desired conversion or input. It's straightforward; even if you are a beginner, just add the recommended filters, and they work great. Drag and drop approach solves most of the coding approach. There aren't many open source GUI-based approaches such as this one. Review collected by and hosted on G2.com.

Not much really. It reduces the coding approach, which might be a habit for developers over time. But everyone is looking for GUI models these days, so might be helpful. On the other hand, it can be difficult for anyone looking for control of every single parameter and full customisation to the details of the approach. Review collected by and hosted on G2.com.

It is a Machine learning based platform for businesses to enhance their experience on different embedded devices for audio-video visuals, sensors on a large scale. Through it's help, all the engineers or developers can solve the problems using Machine learning leading to the solution time to be very quick. Review collected by and hosted on G2.com.

The platform in itself is good enough to use but it can be simplified and made easy to understood by common people also in terms of general analytics rather than just the developers or coders Review collected by and hosted on G2.com.

The user interface which lets a new user to interact and use the platform with confidence without hiding anything from user is one of the best things I like about the Edge Impulse Review collected by and hosted on G2.com.

The interface on the mobile is needs to get improved compared to desktop view. Also the solution section could have more options to access variety and user can apply the knowledge with diversification. Review collected by and hosted on G2.com.

Having a simple and consistent interface to build AI micro systems, with superb control over dataset collection, experiments, deployment (this is the secret sauce of this system, IMHO) Review collected by and hosted on G2.com.

Not so detailed in giving information over NN structure, it would be nice to explore the overall implementation with some more details about "insiders" topics. ARM output in 32bits is someway hard to port to non-mainstream toolchains, like often happens in embedded devices. Review collected by and hosted on G2.com.

Edge impulse makes machine learning possible for Edge devices using an easy Graphical User Based interface. It supports a wide range of devices such as Rasberry Pie, Mobile phones etc. Review collected by and hosted on G2.com.

Support for custom embedded devices could be enhanced. The company could provide a few more features in the developer Edition so that more and more people can try it. Review collected by and hosted on G2.com.