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May 4, 2022

Demystifying Data Pre-processing & Data Wrangling for Data Science | Pariza Kamboj

About This Video

In the current era, Data Science is rapidly evolving and proving very decisive in ERP (Enterprise Resource Planning). The dataset required for building the analytical model using data science, is collected from various sources such as Government, Academic, Web Scraping, API’s, Databases, Files, Sensors and many more. We cannot use such real-world data for analysis process directly because it is often inconsistent, incomplete, and more likely to contain bulk errors. We often hear the phrase “garbage in, garbage out”. Dirty data or messy data riddled with inaccuracies and errors, result in a bad/improperly trained model which in turn might result in poor business decisions and sometimes even hazardous to the domain. Any powerful algorithm is failed in providing correct analysis when applied to bad data. Therefore, data must be curated, cleaned and refined to be used in data science and products based on data science. To perform these tasks, “Data Preparation” is required which includes two methods that are: Data Pre-processing, and Data Wrangling. Most data scientists spend the majority of their time in data preparation.

This workshop was conducted by Pariza Kamboj, Professor at Sarvajanik College of Engineering & Technology (SCET).

Useful resources for this workshop:

In This Video
Professor, Sarvajanik College of Engineering & Technology (SCET)

Dr. Pariza Kamboj is currently associated with Sarvajanik College of Engineering & Technology (SCET) Surat as Professor & HoD in Computer Engineering Department. She has more than 25 years of teaching experience in various reputed engineering colleges in India. She received her Ph. D (Computer Engineering) from MDU Rohtak in year 2011. She did her M.Tech (Comp. Sc. & Engg.) with Distinction from Kururkshetra University (KU), Kurukshetra, Haryana (India) in the year 2006. Her research interest areas are Deep Learning, Machine Learning, IoT, Big Data Analytics, Data Science, Python for Data Science, WSN, Mobile Ad-hoc Networks, Computer Networks, and Network Security. She has published a total of 47 research papers in various International, National Journals, International, National Conferences of repute. She is a member of various professional bodies like Institution of Engineers, Computer Society of India, Indian Society of Technical Education (ISTE), IFERP, ISRD and International Association of Computer Science and Information Technology (IACSIT). She has got published/filed 5 patents in India and Australia. She has done a consultancy and provided a cost effective and efficient solution to the problem titled “Optimizing IVF Predictions and Procedure for Better Outcomes”.

She believes in lifelong learning and keeps on updating her knowledge base with the latest
know-hows and has done approximate 33 trainings on “Deep Learning for computer vision” and “Accelerated Computing with Cuda” from Nvidia Deep Learning Institute and earned certifications on various cutting-edge technologies from NPTEL, Coursera and IBM. She is an IBM Certified Associate Developer for Rational Application Developer for WebSphere Software V6.0. She is a regular contributor on research platforms in the form of Ph.D. Supervisor at Gujarat Technological University, Sarvajanik University, and DPC members in Ph.D. panels of various universities. She is the advisory committee member, organizing committee member, and reviewer of various International Conferences of repute. She loves to share her knowledge and disseminated expert talks on topics of thrust areas in various engineering institutes and workshops. She was/is a member of Board of Studies (Computer Engg.) and Governing Body of various universities in India.

She loves to share her knowledge and disseminated expert talks on topics of thrust areas in various engineering institutes, management institutes and workshops.