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(OPEN FOR HIRING!)

Hi there, I'm Sunil Kappal! šŸ‘‹

Full-time data analytics professional šŸ§‘ā€šŸŽ“šŸŽ“. Service Delivery Leader Analytics (LinkedIN). Freelance Data Analytics Consultant(Portfolio).

šŸ˜Š About me

  • šŸ”­ Iā€™m a seasoned data analytics professional with over 2 decades of industry experience
  • šŸ§° My analytics toolbox contains R, Python, SQL, DAX, Tableau, Power BI, IBM Watson, Microstrategy, MS Excel
  • šŸ¤– Chatbot Frameworks Dialogflo, Botsify
  • šŸŽ° Machine Learning Workflows Azure Ml Studio, Orange Canvas Data Mining, Rapidminer, Knime
  • šŸ“š Predictive Analytics Libraries Rattle, Deducer, R Commander, Numpy, PyCaret, ScikitLearn, Tensorflow, Keras, Pandas, Seaborn, Matplotlib
  • šŸˆø Analytics App Development Framework R Shiny
  • šŸŒ± Iā€™m a life long learner
  • šŸ‘Æ Iā€™m looking to start a data analytics for rookies webinar series
  • šŸ¤” Iā€™m looking to move to the next challenging assignment
  • šŸ’¬ Ask me about anything, but for now, I'm fully open to new projects, collaborations or ideas!
  • āš” Fun fact: Others turn coffee into code; I prefer working out šŸ‹šŸ½ or going out with the bike šŸš“

Languages and Tools:

azure gcp linux mysql photoshop postgresql python scikit_learn sqlite tensorflow

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šŸŽ™ļø Anchor Podcasts
šŸŽ™ļø Spotify
šŸ¦ Twitter
šŸ“· Wordpress

Made with a lot of ā¤ļøā¤ļø by @skappal7

Sunil Kappal's Projects

assessment-tool icon assessment-tool

This repository contains an end to end ML pipeline to predict an organization's analytics maturity based on its KPIs. Current this assessment model is relevant for all the contact center industry

awesome-notebooks icon awesome-notebooks

+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. šŸ˜Ž

business-analytics icon business-analytics

Business Analytics Nanodegree - Learn Excel, SQL and Tableau skills. Four reviewed projects to complete. See the projects website below.

call-center-assessment icon call-center-assessment

This web app predicts how mature your contact center is by looking at the key metrics (sentiment, call duration, non-talk, complaints and repeats). The web app was built in Python using the following libraries: streamlit pandas numpy scikit-learn pickle

ccmaaas icon ccmaaas

This application allows the users to review their contact center performance and see for themselves as to where they stand within their industry based on their performance on key KPIs.

data-science-ipython-notebooks icon data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data-science-with-python icon data-science-with-python

Learn Python programming for data science and its powerful libraries - Numpy and Pandas. Utilize advance SQL queries to investigate relational databases. Use Git and Github to manage versions of your work and publish it in the web.

dataqna icon dataqna

This a TAPEX based streamlit app that can allow users to upload a csv file and ask questions based on the uploaded file.

datasets icon datasets

A collection of datasets of ML problem solving

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