What’s further out there in the machine and deep learning world
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So what’s further out there in terms of machine learning now that you’ve completed this course you’ve
developed a solid understanding of how neural networks work.
Unknowingly you have also acquired a ton of machine learning knowledge and skills that are applicable
to non neural network machine learning approaches.
This course was the important foundation that now allows you to move on to other branches of this cutting
Do you remember the examples of machine learning given in the very first lecture.
Self-driving cars they show recognition smart assistants like Siri.
Well the bad news is that you are not ready to understand exactly how they work right away.
The good news is however that you now know everything necessary to start doing that.
Even better news is that working on business cases like the one we explored would not require techniques
like facial recognition or natural language processing.
In fact only a handful of companies around the world create cutting edge technologies like Siri.
However most large solid respectable entities have a data science division analyzing their business
data and thats where you can fit in.
In any case how are the problems of self-driving cars facial recognition and smart assistants approached.
There are two big extensions on top of neural networks these systems use convolutional neural networks
or CNN’S and recurrent neural networks or Brennen’s.
We are planning on furthering this topic into CNN’s and Arden’s which is why we made two separate lectures
looking into each of them.
But be sure the knowledge you’ve acquired so far will be 100 percent relevant when studying these topics.
We’ll discuss more about CNN’s Art ends at our next lectures.
Thanks for watching.
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