GET SET STUDY

Web Intelligence and Big Data Unit 3 & 4 PYQ 1 (a) How the data from different universe/ sources and projects can be combined in a single reports. Explain. (6) In order to combine data from different universes, sources, or projects into a single report, several techniques can be employed. Here's an explanation of how this can be done: Data Integration: Data integration involves gathering data from various sources and unifying it into a consistent format. This can be achieved through Extract, Transform, Load (ETL) processes, where data is extracted from different sources, transformed to a standardized format, and loaded into a central repository or data warehouse. Data Mapping: Data mapping is the process of matching and aligning data elements from different sources to ensure compatibility. It involves identifying common fields or attributes in the datasets and establishing relationships between them. This allows for a coherent merging of data into a single report. Data Cleans...

Machine Learning End Term Examination 2020 (ETCS 402)  Q1. All questions are compulsory.(2.5x10=25) (a) Explain the goals of machine learning The goals of machine learning are to enable computers to learn from data and make predictions or decisions without being explicitly programmed. The main goals include: Prediction: Creating models that can accurately predict future outcomes or behaviors based on historical data. Classification: Grouping data into categories or classes based on their features. Clustering: Identifying patterns or similarities in data to group them into clusters. Anomaly detection: Identifying unusual or abnormal data points that deviate from the norm. Optimization: Finding the best solution or set of parameters that optimize a specific objective or performance metric. (b) What is bagging? Bagging, short for Bootstrap Aggregating, is a technique used in machine learning to improve the performance and stability of models. It involves creating multiple subsets o...