★ Complete H1 Summary Notes ★ COMP20008: Elements of Data Processing

Description

This note set covers the full subject of COMP20008 – Elements of Data Processing for the 2020 Semester 2 Curriculum, including all covered concepts. The content of these notes were derived from lecture notes, lecture recordings, workshop/tutorial content and examples. These notes include: - Multiple diagrams, tables and highlighted equations that are all clearly set out - Comprehensible diagrams and examples for concepts such as TF-IDF and data visualisations - Summary tables that compare concepts taught, including advantages and disadvantages - Clear separation and format of concepts into topics and sections - Hyperlinked bookmarks of sections that can be easily navigated if opened with a PDF reader software The main topics covered include (but are not limited to): - Data Formats, Gathering and Pre-processing (HTML, XML, JSON etc.) - Correlation, Regression and Classification (incl. decision tree, k-nn etc.) - Data Gathering and Pre-Processing (incl. web crawling/scraping, text, TF-IDF, imputation etc.) - Visualisation and Clustering (incl. k-means, hierarchical, VAT etc.) - Data Linkage and Recommender Systems - Data Security and Social Implications (incl. big data etc.) - Experimental Design (incl. feature selection, dimensionality, splitting etc.) - Shell Basics and Regular Expression Metacharacters These notes helped me obtain an H1 in COMP20008: Elements of Data Processing. They are perfect for both cramming and continuous study throughout the subject. The topics are covered in mostly the same order as they are covered in lectures, and is succinct and compact. All information included is relevant and important for the exam.