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Practical Deep Learning: Image Search Engine

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Ben Cryer
Practical Deep Learning: Image Search Engine

Artificial intelligence is one of the fastest growing fields of computer science today and the demand for excellent AI Engineers is increasing day in and day out. This course will help you stay competitive in the AI job market by teaching you how to create a Deep Learning End-to-End product on your own.

Most courses focus on the basics of Deep Learning and teach you about the very basics of different models. In this course, however, you will learn how to write a whole End-to-End pipeline, from data pre-processing across choosing the right hyper-parameters, to showing your users results in a browser.

The case that we will tackle in this course is an engine for Image to Image Search.

Why should you take this course?

This course is not focused on teaching you Neural Networks (ANNs, CNNs, RNNs…), but teaching you how to apply them in real world cases.

If you haven’t worked on a product that uses Deep Learning before, this is the perfect course for you! Throughout the course we will work together on the Image to Image Search engine, starting from ground zero - image pre-processing, creating a model, training it, then testing. After that we will create a simple web application and use it to serve our model in production.

Another cool thing about this course is that we will use multiple programming languages to create the whole application around the model itself. This will make you not only a better AI Engineer but also get you on the path towards becoming a Full stack AI Engineer.

After taking this course you will guarantee yourself to be one step closer to landing your dream job as an AI/ML Engineer by having your own AI product/project in your portfolio.

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Ben Cryer
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