Reader small image

You're reading from  Developing Kaggle Notebooks

Product typeBook
Published inDec 2023
Reading LevelIntermediate
PublisherPackt
ISBN-139781805128519
Edition1st Edition
Languages
Right arrow
Author (1)
Gabriel Preda
Gabriel Preda
author image
Gabriel Preda

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.
Read more about Gabriel Preda

Right arrow

Metadata exploration

We start by importing the utility functions and classes from the utility scripts for data quality, plot utils, video utils, and face object detection. The following code block shows what we import from the utility scripts:

from data_quality_stats import missing_data, unique_values, most_frequent_values
from plot_style_utils import set_color_map, plot_count
from video_utils import display_image_from_video, display_images_from_video_list, play_video
from face_object_detection import CascadeObjectDetector, FaceObjectDetector
from face_detection_mtcnn import MTCNNFaceDetector

After we load the data files (the train and test samples), we are ready to start our analysis. The following code block checks the types of files in TRAIN_SAMPLE_FOLDER:

train_list = list(os.listdir(os.path.join(DATA_FOLDER, TRAIN_SAMPLE_FOLDER)))
ext_dict = []
for file in train_list:
    file_ext = file.split('.')[1]
    if (file_ext not in ext_dict):
        ext_dict...
lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Developing Kaggle Notebooks
Published in: Dec 2023Publisher: PacktISBN-13: 9781805128519

Author (1)

author image
Gabriel Preda

Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.
Read more about Gabriel Preda