목록Deep Learning (12)

Shakerato

Run code the DL based object detection on raspberry pi 2

Deep Learning based Object Detection source code is herehttps://www.pyimagesearch.com/2017/10/16/raspberry-pi-deep-learning-object-detection-with-opencv/ sudo pip3 install opencv-python sudo pip3 install imutils sudo apt-get install libatlas-base-dev sudo apt-get install libjasper-dev sudo apt-get install libqtgui4 sudo apt-get install libqt4-test open 'pi_object_detection.py' using editor andco..
Research 2018. 6. 30. 17:42
CUDA 9 visual studio integration problem 문제 해결, cuda9 install with vs2017

* 추가 사항 업데이트 (2019-08-19)최신 CUDA 버전을 다운받아 설치하면 visual studio integration 기능을 같이 설치해도문제없이 설치되는 것을 확인하였습니다.아직도 같은 문제가 있으신 분들은 아래 기능을 끄시고 설치하시기 바랍니다. Latest version of CUDA maybe fixed this bug. -------------------------------------------------CUDA 9 (I tested CUDA 9.0, CUDA 9.1, CUDA 9.2)makes "visual studio integration" problemwith Visual Studio 2017 Community latest version When you install CUDA..
Research 2018. 5. 25. 23:22
How to implement next_batch for mini batch gradient descent in deep learning

Full Code: https://www.kaggle.com/pedrolcn/deep-tensorflow-ccn-cross-validationclass TrainBatcher(object): # Class constructor def __init__(self, examples, labels): self.labels = labels self.examples = examples self.index_in_epoch = 0 self.num_examples = examples.shape[0] # mini-batching method def next_batch(self, batch_size): start = self.index_in_epoch self.index_in_epoch += batch_size # When..
Research 2018. 4. 2. 15:29
Role of validation for neural network (deep learning) - validation 역할

Why do we need validation (validation이 필요한 이유)? In order to estimate how well your model has been trained (that is dependent upon the size of your data, the value you would like to predict, input etc) and to estimate model properties (mean error for numeric predictors, classification errors for classifiers, recall and precision for IR-models etc.) - 모델이 학습이 잘 되었는지 측정하기 위해 A set of examples used ..
Research 2018. 4. 1. 21:39
Google colab에서 한국어 NLP 처리 환경 구축

What is Colab (Colaboratory) ?- https://colab.research.google.com- Colaboratory는 기계 학습 교육 및 연구 보급을 돕기 위해 만든 Google 연구 프로젝트입니다.- Jupyter 노트북 환경에서 클라우드 환경에서의 설치 및 실행이 전혀 필요하지 않습니다. - Colaboratory 노트는 Google 드라이브에 저장되며 Google 문서 또는 스프레드 시트에서와 마찬가지로 공유 할 수 있습니다.- Colaboratory는 무료입니다.- Now you can develop deep learning applications with Google Colaboratory on the free Tesla K80 GPU- using Keras, Tens..
Research 2018. 3. 31. 20:35
Deep Learning - GPU memory limitation, How to overcome it?

Limited GPU Memory GPU usually has lesser device memory than host memoryThe latest high-end GPU (such as NVIDIA GPU P100)12–16 GB device memoryHost system memory256GBTrend for deep learning models is to have a “deeper and wider” architectureEspecially, RNN needs a lot of memory 1. First Solution: distributed Deep LearningSource: M. Cho et al., "PowerAI DDL", 2017PowerAI DDL provides a unified in..
Research 2018. 3. 26. 22:36
Prev 1 2 Next