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Intro to Edge AI: Machine Learning + IoT - Maker.io Tutorial | Digi-Key Electronics
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- Опубликовано: 9 ноя 2019
- Artificial Intelligence (AI) is a field of study dealing with teaching computers to behave more like humans or other animals, and it’s been around since the 1950s. Machine Learning, on the other hand, is a subset of AI that deals with computer algorithms that learn from experience to get better at a task or function, such as recognizing faces.
Collecting user data to predict browsing and shopping habits using machine learning has been helping businesses make huge leaps in marketing growth in the last few years. However, collecting, storing, and managing all that “big data” has proven to be troublesome for some companies.
Additionally, the Internet of Things (IoT) is an industry term for connecting non-browser based and non-backbone computing devices to the Internet. While it might not be apparent in our lives as consumers, it has helped industry by being able to automate the monitoring of expensive equipment and track assets as they move about the world.
Edge AI is a somewhat new term that combines these concepts. Instead of moving tons of raw data to a remote server, locally networked computers and embedded devices can utilize machine learning techniques to help alleviate some of the stress of network traffic.
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This looks like an awesome series! Definitely appreciate you cutting through the marketing fluff and admit you're learning this as we go.
I'm a marketing major who just got an internship with a tech company specializing in machine learning and face rec, and your videos are the reason I'm not drowning! Thank you so much!
Appreciate the added history of AI, ML, deep learning, big data, IOT et al.
👍 Superior production value of this video.
Kindest regards.
Excellent Presentation! Thank you♥
definitely deserve more upvotes
I hope to see more ML. Great intro.
Great introduction. Lots of useful information.
Well explained!
Nice introduction to AI.
I keep hearing people describing neural networks as "algorithms". Technically, however, they are but a collection of weight matrices
Yes and no. A "neural network" is a collection of weights (and bias terms) along with the structure of the network (number of nodes in a layer, number of layers, input and output tensor shapes, etc.). It's both the collection of weights and how they're connected. In a way, it's an algorithm (steps performed to get an outcome), but I usually think of the algorithms as the processes needed to train and use the NN.
hey, loving this, but i think your playlist is in reverse order
Thanks for the heads up. All is fixed now. :)
Thank You.
thank you very much!!!!