#Python | Keras Tuner, HyperTuning | #Hyperparameter #Keras #Tensorflow #DeepLearning

RJ Studio’s 109th video is tuning HyperParameters of a Keras Neural Network model in Python. ✨
◕ ◡ ◕

In previous videos, I set reasonable values for various Neural Network HyperParameters based on my experience / learning. Arbitrary choices, however, are most likely suboptimal.

That is why, it is a good idea to conduct tuning in different ways to search for HyperParameter values that can yield better results. 🚀

This video shows you steps to tune your Neural Network model using Keras Tuner!

A lot of explanation in this video is from this link:

Here are some additional helpful links:
(All of above were used in the video)

☆ Video Chapters ☆
0:00 Intro
0:41 Fashion-MNIST dataset
1:27 Rescale & OneHotEncode
2:13 Hypermodel
3:49 Hyperband & EarlyStopping
5:07 Tuning, HyperParameter Search
6:11 Training
6:52 Visualize Accuracies
7:25 Test dataset Evaluation
7:39 Outro

2 Background songs in this video are:
"Smooth Criminal" by David Garrett
"Canon Rock" by Jerry C.
^‿^

Hope my video taught you something new!
And feel free to correct me if I made some mistakes in the comments :)

이번 비디오에서는 케라스 튜너(Keras Tuner)를 이용하여 케라스 신경망 모델의 다양한 하이퍼파라미터들을 튜닝하는 방법을 다루었습니다. ≧◡≦
간단하게 튜닝할 수 있도록 잘 만들어진 기술인 것 같아요!
유익한 정보이길 바랄게요~ 감사합니다.

“In teaching others, we teach ourselves.”

[RJStudio]

0:00 Intro
0:41 Fashion-MNIST dataset
1:27 Rescale & OneHotEncode
2:13 Hypermodel
3:49 Hyperband & EarlyStopping
5:07 Tuning, HyperParameter Search
6:11 Training
6:52 Visualize Accuracies
7:25 Test dataset Evaluation
7:39 Outro