Fastbook notebook_1

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 If you are new to deep learning or stucked like me in the middle of your journey to Artificial Intelligence. 

There is no good source as compared to fastai. I like the practical approach of the fastai and the teaching of the Jeremy's Top Down approach.

I don't want to write a blog about what are the concepts in lecture 1 because there are so many people in the fastai forum who are wonderful in explaining the concepts. If you have any doubt ask in the forum, There is no such thing as a good question or bad question everyone in the community is helping each other out. No one is going to judge you.

I am writing this because you may also face the same problem like me and it may help you in the journey. For each notebook I am going to share my experience and this is about Notebook Lecture 1(Intro). I strongly suggest you watch Jeremy's lectures before going through the notebook.

First oscillation in my mind is which platform I should use for the lecture whether it is google colab or paperspace. What i feel we are just executing the code not doing much complex thing,😅 yup we are doing the complex thing in much easier way using fastai ,colab is user friendly it work fine and it's free you want you may upgrade it pro version that also not cost that much. I never suggest running on the local machine it may upto you.

And the colab version of the fastai is not up to date so before executing the code you must change the runtime to gpu and upgrade fastai by !pip install fastai --upgrade and based on the necessary fastai libraries. And I don't want to complicate things so I used a data block api for every Image classification problem.

And also what i would suggest is go to the fastai documentation, that helps you to understand the functions. Have the motto of "If in doubt, Run the code". 

And you may come across some python code or libraries you may not know. Don't get intimidated in learning everything, just know what they do, you will get in the course journey.

Finally, Don't worry if you don't know something because everyone feels the same. Have the thought that you will learn everything while completing the course. Have a great journey in deep learning.

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