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We bear, we grow; like seeds, like plants.
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We bear, we grow; like seeds, like plants.

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tanaymukherjee/README.md

Welcome to the world of Tanay!

I like to introduce myself as a Statistician and a Data Science Enthusiast with 6 years of experience in analytics domain executing data-driven solutions to increase efficiency, and accuracy in data processing with strong programming expertise. I am experienced at creating regression models, using predictive modeling, and deciphering data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems.

I’ve built my career in a variety of roles and industries, mostly around Analytics and Data Science and have worked with Fortune 500 companies like IBM, Ogilvy (WPP Group), Maersk, and Tesla. I have worked with clients from across the globe and had a wonderful time learning about different cultures.

I am comfortable with R and Python and can use it to solve various problems starting from data wrangling, modeling, automation, etc. I have built multiple projects on ML libraries and my work is accessible via GitHub repositories here. I am pretty confident with SQL in terms of fetching data and doing necessary operations to ensure we have clean and filtered data for processing. Also, have good experience with data visualization tools like Tableau and Google Data Studio.

I have a decent understanding of big data and have worked on AWS wherein I configured and established connections all by myself for multitude of available cloud services. I have worked with EMR, EC2, S3, Athena, Kinesis. I am familiar with Hadoop ecosystem and I am regularly building more on this part to acquire knowledge by implementing projects.

Presently, accelerating fast to get accustomed to the world of deep learning. You got anything to share or discuss? Please feel free to reach out to me at [email protected], and I would love to colloborate.

During free time, I like to read or listen to music. Watching sports is my best way to relax - be it cricket, tennis or soccer, I am in for all. Last read this book called - Crime and Punishment by Fyodor Dostoevsky. If you haven't read it yet, then please do at the first chance.

Want to know more? Connect with me on LinkedIn and we can have more discussions over a cup of Tea/Coffee/Icecream. :)

We bear, we grow; like seeds, like plants.

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  1. Time-Series-Modeling Time-Series-Modeling Public

    A time series is a series of data points indexed in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time …

    Jupyter Notebook 1

  2. Natural-Language-Processing Natural-Language-Processing Public

    Natural language processing is a subfield of linguistics, computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human language…

    Jupyter Notebook

  3. Investigating-NYC-Parking-Violations Investigating-NYC-Parking-Violations Public

    For this project, we will analyze millions of NYC Parking violations since January 2016

    Python 1 1

  4. Deep-Learning-with-PyTorch Deep-Learning-with-PyTorch Public

    PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Re…

    Jupyter Notebook 1

  5. Dissecting-Yelp-Dataset Dissecting-Yelp-Dataset Public

    This dataset is a subset of Yelp's businesses, reviews, and user data. It was originally put together for the Yelp Dataset Challenge which is a chance for students to conduct research or analysis o…

    Jupyter Notebook 2

  6. Dimensionality-Reduction Dimensionality-Reduction Public

    In statistics, machine learning, and information theory, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration by obtaining a…

    Jupyter Notebook 2