Hi there ๐
nhk9680 Goto Github PK
Name: Namhoon Kim
Type: User
Company: Kakao Mobility Crop.
Location: Bucheon, Korea
Name: Namhoon Kim
Type: User
Company: Kakao Mobility Crop.
Location: Bucheon, Korea
Hi there ๐
์ธ์ข ๋ํ๊ต 2019๋ ๋ 1ํ๊ธฐ ์ธ๊ณต์ง๋ฅ ์์
2020-1 Capstone๋์์ธA
์ปดํจํฐ๋น์ ๊ธฐ์ดํธ
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
meching
Open MMLab Detection Toolbox and Benchmark
Daily log 2019.08 ~ 2019.09
2019๋ 2ํ๊ธฐ ํจํด์ธ์
The friendly PIL fork (Python Imaging Library)
์กฐ๊ตํ๋ฉด์ ๊น๋ค๋ก์ ๋ ์ง๋ฌธ ๊ธฐ๋ก
์ด์์ ๋์ ๋์
์ํด์ํดํ์ฌ์ด, ์ฅ์ ๋ฌผ ๋ถ๋ฅ๊ธฐ (2019)
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
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