Big Data in Smart Cities Literature Review Conduct a literature review of big data handling approaches in smart cities including techniques, algorithms, and architectures. You are to review the literature on smart cities and Big Data Analytics and discuss problems and gaps that have been identified in the literature. You will expand on the issue and how researchers have attempted to examine that issue by collecting data – you are NOT collecting data, just reporting on how researchers did their collection. Paper Layout: Title Page Table of contents: Use a Microsoft Enabled Table of Contents feature. Background: Describe the issue, discuss the problem, and elaborate on any previous attempts to examine that issue. Be sure to include techniques, algorithms, and architectures. Research Questions: In the identified problem area that you are discussing, what were the research questions that were asked? Be sure to include main research questions from all the literature you are reviewing. Methodology: What approach did the researcher use, qualitative, quantitative, survey, case study? Describe the population that was chosen. You will discuss the methodology for all the literature you are reviewing. Data Analysis: What were some of the findings, for example, if there were any hypotheses asked, were they supported? Conclusions: What was the conclusion of any data collections, e.g., were research questions answered, were hypotheses supported? Be sure to also include the similarities and differences between the literature.

Week One Assignment (Part A) - Introduction to ML You are expected to be able to program in R. Use Titanic dataset and perform EDA on various columns. Without using any modeling algorithms, and only using basic methods such as frequency distribution, describe the most important predictors of survival of Titanic passengers, e.g. were males or females more likely to survive, were young and rich females more likely to survive than old poor males etc? Please submit the assignment in a word file. Week One Assignment (Part B) - Fundamentals of ML Write a fully executed R-Markdown program and submit a word or html file. The program should merge / join the data files given to you as part of the Santander Bank Case Study. You are then required to perform Exploratory Data Analysis (EDA) along with describing the features of the response variable, visualizing a few predictors, and clearly explaining the findings. Points will be deducted in case the explanation and commentary is missing in the submission.  Visit the Kaggle website for the Santander Bank classification challenge and describe the main problem. Also describe various challenges and limitations of this case analysis.   https://www.kaggle.com/c/santander-customer-transa..  https://faulkneracademyorg-my.sharepoint.com/:u:/g... use Santander Customer Transaction Prediction CSV file for EDA.   

Week 8 Discussion When thinking about data visualization, it is important to understand regular expressions in data analytics.  Therefore, note the importance of data visualizations and choose two types of expressions (* - wildcards for example) and discuss the difference between the two types of expressions.