Skip to content

Instantly share code, notes, and snippets.

Vivek Amilkanthawar vivek081166

Block or report user

Report or block vivek081166

Hide content and notifications from this user.

Learn more about blocking users

Contact Support about this user’s behavior.

Learn more about reporting abuse

Report abuse
View GitHub Profile
View tpot.py
from tpot import TPOTClassifier
from sklearn.datasets import load_digits
from sklearn.model_selection import train_test_split
digits = load_digits()
X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target,
train_size=0.75, test_size=0.25)
tpot = TPOTClassifier(generations=5, population_size=50, verbosity=2)
tpot.fit(X_train, y_train)
View mlbox_auto_ml_house_prices.py
# Inputs & imports : 必要があるのはそれだけです!
from mlbox.preprocessing import *
from mlbox.optimisation import *
from mlbox.prediction import *
paths = ["../input/train.csv","../input/test.csv"]
target_name = "SalePrice"
View transmogrif_ai.py
import com.salesforce.op._
import com.salesforce.op.readers._
import com.salesforce.op.features._
import com.salesforce.op.features.types._
import com.salesforce.op.stages.impl.classification._
import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession
implicit val spark = SparkSession.builder.config(new SparkConf()).getOrCreate()
import spark.implicits._
View auto_keras.py
from keras.datasets import mnist
from autokeras import ImageClassifier
from autokeras.constant import Constant
if __name__ == '__main__':
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train = x_train.reshape(x_train.shape + (1,))
x_test = x_test.reshape(x_test.shape + (1,))
clf = ImageClassifier(verbose=True, augment=False)
clf.fit(x_train, y_train, time_limit=30 * 60)
View h2o_automl.py
import h2o
from h2o.automl import H2OAutoML
h2o.init()
# サンプルバイナリ結果トレイン/テストセットをH2Oにインポートする
train = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_train_10k.csv")
test = h2o.import_file("https://s3.amazonaws.com/erin-data/higgs/higgs_test_5k.csv")
# 予測子とレスポンスを特定する
View auto_sklearn.py
import sklearn.model_selection
import sklearn.datasets
import sklearn.metrics
import autosklearn.regression
def main():
X, y = sklearn.datasets.load_boston(return_X_y=True)
feature_types = (['numerical'] * 3) + ['categorical'] + (['numerical'] * 9)
@vivek081166
vivek081166 / mlbox-auto-ml-house-prices.ipynb
Last active Apr 23, 2019
mlbox-auto-ml-house-prices.ipynb
View mlbox-auto-ml-house-prices.ipynb
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
View model.py
from keras.callbacks import ReduceLROnPlateau
from keras.utils.np_utils import to_categorical
import keras.backend as K
from keras import regularizers
from keras.layers import Lambda
from keras.layers.convolutional import Conv1D, MaxPooling1D
from keras.layers.core import Activation, Dense
from keras.layers.normalization import BatchNormalization
from keras.models import Sequential
import numpy as np
View process_data.py
import os
import pickle
from glob import iglob
import numpy as np
import librosa
DATA_AUDIO_DIR = './audio'
TARGET_SR = 8000
OUTPUT_DIR = './output'
OUTPUT_DIR_TRAIN = os.path.join(OUTPUT_DIR, 'train')
View blog20190409_1.py
import os
import pickle
from glob import iglob
from shutil import rmtree
import numpy as np
from model_data import read_audio_from_filename
DATA_AUDIO_DIR = './audio'
TARGET_SR = 8000
OUTPUT_DIR = './output'
You can’t perform that action at this time.