Скачать или смотреть Podcast Data Science and Engineering blueprint

This short podcast offers an essential training path covering the fundamental principles of data science and data engineering, adhering to the competencies recommended by the Association for Computing Machinery (ACM).
To learn more, see https://mybook.to/V0QAMPh
The text emphasizes the use of Python and its key libraries, such as Pandas and Scikit-learn, along with the standardized CRISP-DM methodology for problem solving. Subsequent sections detail crucial techniques for data acquisition, preparation, and cleansing (such as missing value handling and entity resolution), all supported by visualization methods for data exploration (EDA). Finally, the textbook explores modeling concepts, evaluation metrics for regression and classification, the different categories of machine learning (supervised and unsupervised), and advanced deep learning architectures such as transformative neural networks.