train_age_ds = train_ds.map(preprocess_age_data, num_parallel_calls=BATCH_SIZE).batch(BATCH_SIZE).prefetch(tfds.AUTOTUNE) train_gender_ds = train_ds.map(preprocess_gender_data, num_parallel_calls=BATCH_SIZE).batch(BATCH_SIZE).prefetch(tfds.AUTOTUNE) valid_ds = tfds.Dataset.from_tensor_sli...
dataset_blend_train = np.zeros((Xtrain.shape[0],len(set(y.tolist())) # dataset_blend_test = np.zeros((Xtest.shape[0],len(set(y.tolist())) dataset_blend_test_list=[] loglossList=[] for i, (train, test) in enumerate(skf): # dataset_blend_test_j = [] X_train = Xtrain...
TensorFlow 2.0 - tf.data.Dataset 数据预处理 & 猫狗分类 datadatasetimagesizetensor 项目及数据地址:https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition/overview Michael阿明 2021/02/19 2.5K0 【Kaggle竞赛】迭代训练模型 tensorflow神经网络深度学习 CV领域中,在完成数据准备工作和设计定义好模型之...
preprocessing import StandardScaler from sklearn.svm import SVC # 使用支持向量机数据需要归一化 svm = make_pipeline(StandardScaler(), SVC(gamma='auto')) svm.fit(X_train_res, y_train_res) Out[54]: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 Pipeline(steps=[('standardscaler', ...
What would you like to do with this data? You are a professional data analyst, please try to conduct some research on yourself. Sure, I can conduct an exploratory data analysis (EDA) on this dataset. The goal of EDA is to understand the main characteristics of the data, identify patterns...
如果你的方向是stat相关,比如stat,data science啦,OR啦,我比较推荐有一个Kaggle的经历,因为Kaggle比赛非常地target在对real dataset的处理上,而且每个比赛都有个专栏kernel,参加比赛的data scientist会分享他们的idea/code,我觉得这样的经历能让人快速高效提升实战技能。 现在对我们系的学弟学妹,我都建议他们去做个Kagg...
datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, # set each sample mean to 0 featurewise_std_normalization=False, # divide inputs by std of the dataset samplewise_std_normalization=False, # divide each input by its std...
encodingdata-sciencemachine-learningdeep-learningpipelineoptimizationkerasregressionpredictiondistributedkagglexgboostclassificationlightgbmpreprocessingdriftautomlstackingautomated-machine-learningauto-ml UpdatedAug 6, 2023 Python Fast and customizable framework for automatic ML model creation (AutoML) ...
###缺失值处理fordatasetindata_cleaner:#用中位数填充 dataset['Age'].fillna(dataset['Age'].median(),inplace=True)dataset['Embarked'].fillna(dataset['Embarked'].mode()[0],inplace=True)dataset['Fare'].fillna(dataset['Fare'].median(),inplace=True)#删除部分数据 ...
备注:数据放在data/kaggle_original_data目录 代码语言:javascript 代码运行次数:0 运行 AI代码解释 import os, shutil # The path to the directory where the original # dataset was uncompressed(原始数据集解压目录的路径) original_dataset_dir = 'data/kaggle_original_data' # The directory where we will ...