Recurrent Neural Networks, Long Short Term Memory and the famous Attention based approach explained
When you delve into the text of a book, you read in the logical order of chapter and pages and for a good reason. The ideas you form, the train of thoughts, it’s all dependent on what you have understood and retained up to a given point in the book. …
Paper summary and code.
Deep convolutional neural networks have led to a series of breakthroughs for image classification tasks.
Challenges such as ILSVRC and COCO saw people exploiting deeper and deeper models to achieve better results. Clearly network depth is of crucial importance.
Due to the difficult nature of real world tasks or problems being thrown at deep neural networks, the size of the networks is bound to increase when one wants to attain high levels of accuracy on deep learning tasks. …
I came across multiple solutions to access files from Google drive in Colab notebooks asking to install wrappers or utilities and what not.
However, accessing files from Google drive can be done just with these 2 lines of code:
from google.colab import drivedrive.mount('/content/drive')
This will generate a url in Colab, click that, which will open up a new tab, choose your Google account, allow access. This will generate a token, copy that and paste back in the blank field in Colab.
After the drive has been mounted follow the next step.
Now to access files from drive: prefix this…