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IshanDandekar t1_jedz4db wrote

Projects. Only way to test what you have learned is projects. In Andrew Ng's deep learning course, he has assignments pertaining to a topic/application of deep learning. Easiest way to expand this is to make a whole project out of it. Best way to show your skills.

As you said, yes there are resources to get weights for models, look into model zoos. Hope this helps!

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IshanDandekar t1_jedzcud wrote

Look into tutorials or projects published on YouTube maybe, even that is a great source. The main idea to copy someone's project in beginner stage, is to get inspired by them and then later do what you want and build upon it. Right now you have the theoretical knowledge, but programming will also come into the picture when you are on a data science job

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adharanda11 OP t1_jee51x0 wrote

I was also thinking about this to gain a basic experience of how projects are made and structured.

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IshanDandekar t1_jee9uy6 wrote

You wouldn't want to go into designing machine learning systems and life cycle right now. Just build projects. Don't get stuck into a cycle of MOOCs

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adharanda11 OP t1_jeec8nu wrote

How will I build projects if I don't know how to use tensorflow?

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IshanDandekar t1_jeecfu0 wrote

Tensorflow is used to make neural networks. Start with simpler machine learning algorithms. Look into the Scikit-learn library. Scikit-learn is used for simpler and more commonly used machine learning algorithms. Look into kaggle tutorials for better understanding. Hope this helps!

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Sa1g t1_jefrkw4 wrote

After you have played with scikitlearn, spend some time studying its endpoint (it's like an industry standard), then go on and play with tensoflow/torch

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