Assignment: Data Management for AI Applications

Objective: To understand and apply the concepts and techniques of data management for AI applications.

Tasks: Choose an AI application domain that interests you, such as natural language processing, computer vision, recommender systems, etc. Describe the main goals and challenges of the domain, and the types of data that are used or generated by the AI systems in that domain. Find and analyze a publicly available dataset related to your chosen domain. You can use online sources such as Kaggle, UCI Machine Learning Repository, Google Dataset Search, etc. Provide a brief overview of the dataset, such as its size, format, features, labels, etc. Explain how the dataset can be used for AI purposes, such as training, testing, evaluation, etc. Perform data management tasks on the dataset using appropriate tools and methods. You can use any programming language or framework that you are familiar with, such as Python, R, SQL, etc.

You should cover at least three of the following data management areas:

Classification: Obtain, extract, and structure data from documents, photos, handwriting, and other media using AI techniques such as optical character recognition (OCR), natural language processing (NLP), computer vision (CV), etc. Cataloging: Help to locate data using AI techniques such as metadata extraction, semantic annotation, data discovery, etc. Quality: Reduce errors in the data using AI techniques such as data cleaning, validation, verification, imputation, etc. Security: Keep data safe from bad actors and make sure its used in accordance with relevant laws, policies, and customs using AI techniques such as encryption, anonymization, access control, auditing, etc. Data integration: Help to build master lists of data using AI techniques such as entity resolution