A Comprehensive Hands-on Guide to Regression analysis - Machine Learning
A Regression Analysis guide with a hands-on exercise using a scikit-learn library to solve a real-time use case.
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+1 (906) 370 7479
Hello! I'm Prateek, an aspiring Data Scientist with a penchant for making life easier with Machine Learning.
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My name is Prateek, a 12X Certified Data Science professional with 5+ years of work experience in delivering data-driven decisions and insights to clients across the Logistic and Healthcare domain. Highly skilled in machine learning, data visualization, and designing ETL pipelines.
Prateek Goyal
prateekg@mtu.edu
13 June 1992
+1 (906) 370 7479
Graduate Student
Houghton, MI
The things in which I've invested my huge chunk of time.
A decade's hard work!
Specialization:
Machine Learning and Artificial Intelligence
Coursework:
• Intro to Data Science
• Regression Analysis
• Machine Learning
• Advanced Artificial Intelligence
• Advanced Data Mining
• Information Systems Management and Data Analytics
• Predictive Modelling
Cumulative GPA:
4/4
Coursework:
• Algorithms and Data Structures
• Advanced Data Structures
• Theory of Computation
• Advanced Database Management System
• Advanced Computer Architecture
• Software Architecture
• Compiler Construction
• Software Development Methodologies
• Software Testing
GPA:
First Class with Distinction
Company:
Cisco Systems Inc, TX, USA
Company:
Hinge Global, OH, USA
Responsibilities:
• BI Dashboard Developer: Designed an OnDemand Business Centric reports using a data cube approach; enabled end-user to fetch reports using the drag-n-drop dimensions.
• Data Engineer: Designed and developed fully automated ETL pipelines for data synchronization between systems using code reusability approach, reduced sync-time by 95.8%. Skills: Python, Oracle, SQL, Task Scheduler.
• Data Engineer: Created Log parsing scripts using Python, automated email communication using mail transfer protocol for handling script failure/error. Skills: Python, SMTP, Batch Scripts.
Company:
Visteon Corporation, MI, USA
Responsibilities:
• Legacy System: Automated ETL processes; performed operations such as cleaning, transformation, and ensuring integrity between various environments. Techniques Used: Python, SQL, SMTP, Batch Scripts, Logfile Parsing.
• US-based automotive electronics supplier: Integrated multiple logical data cubes into a single data model; developed on-demand Business Centric reports using a drag-drop feature. Techniques Used: Siemens Teamcenter Reporting & Analytics tool, Oracle.
Company:
SAS Research & Development Institute, India
Responsibilities:
• US-based major Healthcare: Developed ETL pipelines for processing terabytes of PHI data, performed data integration from varied sources, data pre-processing, and feature engineering; making data ready for downstream purposes. Techniques used: SAS Macros, MapReduce, HDFS, Statistics, Linux.
• US-based major Healthcare: Led the development and maintenance of ongoing dashboards, reports, analyses, etc., to drive health science-related decisions and communicate real-time feeds to Doctors and Scientists; resulted in saving 300+ lives last year. Techniques Used: Tableau, SAS VA, SAS Cloud Analytic Services, Hadoop.
Company:
TATA Consultancy Services (TCS), India
Responsibilities:
• Danish Logistic Company: Build a route optimization model for the transportation of empty containers; saved up to $4 million yearly. Techniques Used: SAS, Oracle, PL-SQL.
• Danish Logistic Company: Engaged in data profiling to optimize an existing data model; reduced report execution time from ~36 hours to under 10 minutes; enabled the client to get live updates of all in-transit containers on the fly. Techniques Used: Data Warehousing, OLAP, SAP BusinessObjects, IDT, MySQL.
Powering business growth through data driven insights.
Implemented my learning to solve some real-life challenges.
It's always a great idea to acknowledge one's work!
The best way to learn something is to teach something.
A Regression Analysis guide with a hands-on exercise using a scikit-learn library to solve a real-time use case.
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Perform data preprocessing steps using Python3 before any Machine Learning model development Life cycle.
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A quick Matlab/Octave hands-on exercise with various examples to compute many complex calculations effectively.
Read MoreIt's good to know about each other.
+1 (906) 370 7479
prateekg@mtu.edu
11500 Jollyville Rd, Austin, TX, USA