Machine Learning Engineer & Senior Software Enigneer
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3+ years of experience in Software Engineering/Development using Python
2.5+ years of experience in Machine Learning/ Data Science Engineering
After my successful internship at Teradata in 2016 is what made me dwell in distance of data sciences, Artificial Intelligence, and machine learning.
The roadmap turned towards Data Sciences & AI made me join Northbay solutions which, in fact, one of Data Analytics and ML Amazon’s partner.

You can find my full CV here.

My mission is to create recommendation engines, perform data analytics with open tools to lower the barrier of entry for machine learning applications, promote reproducible science and democratize the access to high-quality machine learning algorithms.

I like programming and problem solving although I make basic mistakes on hackerrank and codality

Specializations


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Amazon Web Services Certified Professional
Specialization in Python Programming
Specialization in Code Quality/Documentation
Specialization in Statistics & Mathematics
Specialization in Algorithms(hardest)
Specialization in Machine Learning
Specialization in Statistics with Python
Specialization in Probability Theory
Specialization in Teradata SQL
Specialization in IOT & Quantum Computing(upcoming)
More than 100+ certification of completion

Certification Verification

Projects


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Dun & Bradstreet POC

role: Tech Lead: Data Science & Neptune

Semantic Web Analysis with Graph database automation for their recommendation engines. A real time full query optimization for semantic relations within Companies/Organization.


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Wolters Kluwer

role: Machine Learning Engineer

Textual Classification for sec.org documents consisting of multiclass and multilabel classes, including custom evaluation criteria and automation of classification and self tunable algorithms.


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Carnival

role: Machine Learning Engineer

Time Series Customer Loyalty Analysis & Predictive Analytics on 50 TB's of data. Mapping of 1000+ columns to 40 useful features which later onward counted in Customer Loyalty Analysis and Predictive Analytics for products.

CONFIDENTIAL CONFIDENTIAL Github Repository

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EVision

role: Alexa SkillKit Engineer

Automation of a Virtual Assistant, Alexa interaction with Evision Education Platform, manipulation and others.

CONFIDENTIAL Project website CONFIDENTIAL Github Repository

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Intelligize

role: Machine Learning Engineer

Document Grain based classifiation based on their target audience to which organization the problem/law relates to, A Recommendation Engine which works mainly for classification of sub sectional graining of sec.org documents.

CONFIDENTIAL Project website CONFIDENTIAL Github Repository


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Keurig

role: Alexa/ NLP Engineer

Artificial Intelligent assistant integration with (data lake) Datawareware house for automation along with BI users.

CONFIDENTIAL Project website CONFIDENTIAL Github Repository

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PYSHA

role: Machine Learning and NLP Engineer

A virtual assistant with intelligence and huge API access for its intelligence acting as information retrieval, extractor engineer. Along with chatbot and OS automation.

Project website Github Repository

My Famous Videos


Python & Beginner: The two tools that love each other

Python Programming for Absolute Begineer(when I sucked at python), full series is 2h

You will start by learning about python Programming with complete beginner experience. Basic knowledge of usage of computer is required so don't get cocky.

Famous Channel

Experience


Favourite Sheet


The (notorious) cheat-sheet

A guide to picking a model in scikit-learn based on the dataset and task. It tries to give a point to start for beginners, not absolute rules, so take it with a grain of salt.

Blog post Interactive version