Hello :) Today is Day 34!
A quick summary of today:
- today I covered the final part of TensorFlow: Data and deployment specialization
When creating an app for iOS/Android, it would be nice to follow the following step-by-step guide.
Set up the model in the desired platform > process input provided by the user > pass the input to the model > get results and show them
Then, I learned about tensorflow datasets (tfds).
Cache can be used to improve performance
Memory cache provides faster access time and fits well with small to medium-sized datasets. Disk cache provides persistence and scalability and fits well with large datasets
Next, I learned a bit about TensorBoard
You can see the mean and standard deviation for each epoch on the TensorBoard (Cool!)
In addition, if you create a classification model, you can also see the confluence matrix of each epoch
For example, epoch 1:
Epoch 3:
Lastly, learned about Federated learning
Federated learning is a technology that learns a global model in a decentralized situation in which a central server and local clients cooperate with each other. It has advantages in terms of data privacy and communication efficiency, and it requires solutions to problems such as completely decentralized learning, and there are several challenges such as model learning in situations where data is unevenly distributed.
Actually, I was going to certify TF developer today, but my card kept getting rejected :/ (I emailed Google)
If I cannot do that, my next options are:
I have to decide tomorrow
That is all for today!
See you tomorrow :)