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Profile Summary

  •  Result-driven IT professional with overall 14 years of experience in Software product development of which 4 years in Data Science.
  •  Lead Analytical projects to drive insights and actions to improve operational efficiencies, customer
  • experience, revenue growth, and profitability as part of the Digital Transformation
  • Hands-on experience with end-end solution delivery of Data & Analytics applications involving structured and unstructured data.
  • Experience in both Supervised and Unsupervised learning including Deep Learning, Regression, Clustering, Classification, Time-series Analysis, Anomaly detection, Text Mining, NLP.
  • Experience in deep learning-based OCR solutions(Connectionist text proposal network, Google Vision
  • Experience in Abbyy Vantage, Abbyy Flexi Capture, UiPath based OCR solutions(Orders, Bill of lading, Invoices, Statements, balance sheets, Covid-19 financial benefit forms)
  • Experience in Deep Learning-based Chatbots(RASA, AMAZON LEX)
  • Contracts Intelligence management solutions
  • Experience with data visualization tools /libraries such as Plotly Dash, Matplotlib, Seaborn, Tensor Board, Tableau, D3, R Shiny.
  • Solid understanding and expert knowledge of Agile and Traditional Project Management Principles/ Practices with the ability to blend them to fit project and business environment; well versed in Waterfall, Agile methodologies
  • Experienced in analyzing situations by using a systematic approach and identifying patterns and connections between them for creating an amicable and transparent environment while promoting employee communication across the organization 


Certification

  •  Google Big Data and Machine Learning Fundamentals- Google
  •  Rasa Developer Certification
  •  Deep Learning –Andrew Ng, IIT Kharagpur.
  •  Machine Learning L2 certification - Wipro
  •  Certified Scrum Master(CSM) –Scrum Alliance License: 000665091
  •  Project Management Professional (PMP)-KnowledgeHut, Reliance JIO
  •  Siebel 7.7 Core Consultant Certified
  •  Oracle Policy Automation Rule Author Certified (OPA)

Achievements

  •  Runner up in TechGig 2019 Artificial Intelligence,NEC Hackathons.
  •  Received Top Coder award for my contribution to Philips Client in Wipro
  •  Received Pragati award for ML contribution to Philips M2O Project
  •  Received Eagle Squad award, CO awards for my data science contribution to MDTA project
  •  Received SPOT, Project Oscar, GEM, Innovation awards in Oracle.

Advising Module Brief

Machine learning and Deep Learning:

  1. Career Counseling 
  2. Training
  3. Mentoring

Availability Time

MON-FRI :

21:00 To 22:00

SAT-SUN :

09:00 To 22:00


Current Location

Bangalore

Language Proficiency

English, Hindi, Telugu,Kannada

Education


1Graduation (Computers)

2Master Degree (MBA)

Advising Module

1 . Machine Learning with Python

  • Duration (In Hours): 35
  • Total Sessions: 30
  • Duration (In Months): 1 Months
  • Added On: 07-Jun-2020
  • Specific Details : Hand crafted comprehensive machine learning course with real time examples
  • Education Level: Degree Holders,Graduates,PostGraduate
  • Criteria: Art,Management,Science,Technology
  • Topics Covered

    •Introduction to machine learning

    •Python Basics

    •Data Preprocessing with pandas

    •Matplotlib and Seaborn Visualizations

    •Statistics Basics

    •Measurement scale

    •Sampling

    •Types of variables

    •Types of statistics

    •Measure of central tendency

    •Measure of variability

    •Plots

    •Skewness

    •Kurtosis

    •Central limit theorem

    •Probability

    •Statistics Basics

    •Probability

    •Combinations and Permutations

    •Baye’s Theorem

    •Confidence Interval

    •Pearson correlation coefficient

    •Hypothesis test

    •Decision Errors

    •Z,T tests

    •Anova(one way, two way)

    Chi Square test

    •Regression

    •Regression basics

    •Simple Linear Regression

    •Gradient Descent algorithm

    •Polynomial Regression

    •Ridge and Lasso Regression

    •Multi nominal Regression

    •Classification

    •Classification basics

    •Training and Loss

    •Threshold

    •Accuracy

    •Precision and Recall

    •Roc Curve and AUC

    •Bias and Variance

    •Cross Validations

    •Grid and Random Search

    •Im-balanced datasets

    •Principal Component Analysis

    •PCA basics

    •Decision Trees

    •Tree basics

    •Random Forests

    •ADA Boost

    •Time Series

    •ARIMA

    •SARIMA

    •Recommendation systems

    •SVM

    •K-NN

    •Clustering

    •Clustering basics

    •K Means Clustering

    •Hierarchical Clustering

    •DB Scan clustering

    •NLP Basics

    •Introduction to Neural network

    •Reading data from NOSQL ,SQL,HDFS

    •Productionizing the models

    •Plotly dash visualizations

    •Interview Preparation Tips and Tricks

    •use case



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