- 画面上の位置を「右」に設定する
- 「Dock を自動的に隠す」を入にする
- キーボード → 「キーのリピート」を最速に、「リピート入力認識までの時間」を最短にする
SDK_TOOLS_URL="https://dl.google.com/android/repository/commandlinetools-linux-11076708_latest.zip" | |
ANDROID_HOME="/home/ubuntu/repos/android-sdk" | |
export ANDROID_HOME="${ANDROID_HOME}" | |
mkdir -p ${ANDROID_HOME}/cmdline-tools | |
mkdir -p ${ANDROID_HOME}/platforms | |
mkdir -p ${ANDROID_HOME}/ndk | |
wget -O /tmp/cmdline-tools.zip -t 5 "${SDK_TOOLS_URL}" | |
unzip -q -o /tmp/cmdline-tools.zip -d ${ANDROID_HOME}/cmdline-tools | |
rm /tmp/cmdline-tools.zip |
html, body { | |
margin: 0; | |
padding: 0; | |
} | |
.ant-box { | |
position: relative; | |
width: 400px; | |
height: 400px; | |
border: 1px solid #ddd; | |
} |
https://flutter.dev/docs/get-started/install/macos
$ cd ~/Projects
$ unzip ~/Downloads/flutter_macos_v1.9.1+hotfix.2-stable.zip
$ export PATH="$PATH:/Users/rakuishi/Projects/flutter/bin"
$ source ~/.bash_profile
$ flutter precache
# 0.1176554 | |
def homework(train_X, train_Y, tokenizer_en, tokenizer_ja): | |
import numpy as np | |
from keras.models import Model | |
from keras.layers import Input, Embedding, Dense, LSTM | |
emb_dim = 256 | |
hid_dim = 256 | |
en_vocab_size = len(tokenizer_en.word_index) + 1 |
Month | International airline passengers: monthly totals in thousands. Jan 49 ? Dec 60 | |
---|---|---|
1949-01 | 112 | |
1949-02 | 118 | |
1949-03 | 132 | |
1949-04 | 129 | |
1949-05 | 121 | |
1949-06 | 135 | |
1949-07 | 148 | |
1949-08 | 148 | |
1949-09 | 136 |
# -*- coding: utf-8 -*- | |
# https://rakuishi.com/archives/getting-started-with-keras/ | |
from keras.datasets import mnist | |
from keras.utils import to_categorical | |
from keras.models import Sequential | |
from keras.layers import Dense, Activation | |
(x_train, y_train), (x_test, y_test) = mnist.load_data() | |
x_train.shape, y_train.shape, x_test.shape, y_test.shape |
def homework(train_X, train_y, test_X): | |
import keras | |
from keras.models import Sequential | |
from keras.layers import Dense, Conv2D, MaxPooling2D, Flatten, Input, Activation, Dropout | |
from keras.layers.normalization import BatchNormalization | |
from keras import optimizers | |
from keras.preprocessing.image import ImageDataGenerator | |
gcn_whitening = ImageDataGenerator(samplewise_center=True, samplewise_std_normalization=True) | |
gcn_whitening.fit(train_X) |