Practical Data Analysis

Practical Data Analysis Hector Cuesta, Sampath Kumar
Key FeaturesLearn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your dataApply Machine Learning algorithms to different kinds of data such as social networks, time series, and imagesA hands-on guide to understanding the nature of data and how to turn it into insightBook DescriptionBeyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service.This book explains the basic data algorithms without the theoretical jargon, and you’ll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark.What you will learnAcquire, format, and visualize your dataBuild an image-similarity search engineGenerate meaningful visualizations anyone can understandGet started with analyzing social network graphsFind out how to implement sentiment text analysisInstall data analysis tools such as Pandas, MongoDB, and Apache SparkGet to grips with Apache SparkImplement machine learning algorithms such as classification or forecastingAbout the AuthorHector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time.Dr. Sampath Kumar works as an assistant professor and head of Department of Applied Statistics at Telangana University. He has completed M.Sc., M.Phl., and Ph. D. in statistics. He has five years of teaching experience for PG course. He has more than four years of experience in the corporate sector. His expertise is in statistical data analysis using SPSS, SAS, R, Minitab, MATLAB, and so on. He is an advanced programmer in SAS and matlab software. He has teaching experience in different, applied and pure statistics subjects such as forecasting models, applied regression analysis, multivariate data analysis, operations research, and so on for M.Sc. students. He is currently supervising Ph.D. scholars.Table of ContentsGetting StartedPreprocessing DataGetting to Grips with VisualizationText ClassificationSimilarity-Based Image RetrievalSimulation of Stock PricesPredicting Gold PricesWorking with Support Vector MachinesModeling Infectious Diseases with Cellular AutomataWorking with Social GraphsWorking with Twitter DataData Processing and Aggregation with MongoDBWorking with MapReduceOnline Data Analysis with Jupyter and WakariUnderstanding Data Processing using Apache Spark Categories:
Computers – Databases
Year:
2016
Edition:
2
Publisher:
Packt Publishing
Language:
english
Pages:
338 / 330
ISBN 10:
1785289713
ISBN 13:
9781785289712
File:
273 MB