Echo Dot (3rd Gen) - Smart speaker with Alexa - Charcoal

Use your voice to play a song, artist, or genre through Amazon Music, Apple Music, Spotify, Pandora, and others. With compatible Echo devices in different rooms, you can fill your whole home with music.

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Wireless Rechargeable Battery Powered WiFi Camera.

Wireless Rechargeable Battery Powered WiFi Camera is home security camera system lets you listen in and talk back through the built in speaker and microphone that work directly through your iPhone or Android Mic.

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Supervised vs. Unsupervised Learning — Use & Myths! | by Onlim



Have you ever wondered whether there is a connection between the weather and your sales figures or how your sales will develop in the next few months? If so, you have probably often wished for a “ for these problems. You provide your problems as input and on the other side, the solution magically appears.

But isn’t this exactly what algorithms in machine learning already do? Let’s find out.

First of all, it is important to understand what an algorithm actually is. Simply put, an algorithm is a way of solving a problem. For example, when developing chatbots, we are faced with the problem that we need to know which questions our users will ask.

For this purpose, we use an algorithm for topic recognition. With the help of this algorithm, we try to understand which topics are important to the users and which questions are asked the most frequently.

However, these algorithms have to be constantly trained and improved. No matter how well you know the users of your chatbot and their problems: New topics or questions can always arise that you have never even thought of.

You can distinguish between two types of training for an algorithm: Unsupervised Learning and Supervised Learning. These differ mainly in the type of data and the use cases.

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