AMA #7 Questions & Answers.

 

Your most burning questions from AMA #7.

 

Laurence introduced this book in the intro workshop: http://shop.oreilly.com/product/0636920052289.do. Was wondering if there are other resources that would help us learn how to use TensorFlow in a production environment?

If you’re new to deep learning, I suggest using Pytorch, fast.ai, or Keras. This could help you get started in deep learning faster as they are easier to learn. Check out: https://classroom.udacity.com/courses/ud188. Pytorch is a fast and versatile framework for deep learning. The link will give you the different deep learning models which you can learn and implement. If you’re wondering about the difference, Tensorflow/ Keras is backed by Google, while PyTorch is backed by Facebook. Fast.AI is built on top of PyTorch to make it easier to learn.

There have been several datasets used in the statistical courses for the purpose of practising. May I know if these datasets are accessible beyond the courses? Do you have any recommendation on public datasets that we can work with learning purposes?

Check out Kaggle for public datasets.

What is the last date we need to complete the 3-month DataCamp track by?

8 February 2019.

Will the certificates be issued on 8 February upon meeting all requirements?

We will need time to confirm all details, so you’ll likely receive the certificates by end February 2019.

Watch AMA #7 here for a quick recap. 

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