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https:// | https:// | ||
+ | |||
+ | ==== DAsP 데이터아키텍쳐 자격검정 ==== | ||
+ | https:// | ||
==== Tensorflow Developer Certification ==== | ==== Tensorflow Developer Certification ==== | ||
+ | https:// | ||
+ | ===환경설정=== | ||
+ | * https:// | ||
+ | * CUDA 오류 : https:// | ||
+ | |||
+ | * Tensorflow버전에 따른 CUDA, CUDNN 맞는 버전 : https:// | ||
+ | * failed to create cublas handle: | ||
+ | <code python> | ||
+ | import tensorflow as tf | ||
+ | gpu = tf.config.experimental.list_physical_devices(' | ||
+ | try: | ||
+ | tf.config.experimental.set_memory_growth(gpu[0], | ||
+ | except RuntimeError as e: | ||
+ | print(e) # Error 발생하면 Error 내용 출력 | ||
+ | </ | ||
+ | |||
+ | |||
+ | |||
+ | * | ||
+ | |||
===응시후기=== | ===응시후기=== | ||
+ | [[https:// | ||
https:// | https:// | ||
https:// | https:// | ||
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* Coursera: DeepLearning.AI TensorFlow Developer lecture note and assignments for tensorflow certificate. | * Coursera: DeepLearning.AI TensorFlow Developer lecture note and assignments for tensorflow certificate. | ||
* https:// | * https:// | ||
+ | * https:// | ||
+ | ===Tip 정리=== | ||
+ | 1. 데이터 셋 정확한 비율로 올바르게 분할했는지 | ||
+ | - 문제 조건에 맞는 in/output shape 확인 | ||
+ | - Data Augmentation | ||
+ | 2. 단순히 epoch 늘려보기 | ||
+ | - ReLU 대신 LeakyReLU | ||
+ | - learning rate 조금씩 키우기 (epoch 늘리기엔 학습시간 부족할 때) | ||
+ | 3. 추가 레이어 | ||
+ | - 레이어 종류 | ||
+ | - Dropout | ||
+ | - Conv. 레이어 필터 수 줄여보기 | ||
+ | 4. Callback : early stop | ||
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