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About

Hi πŸ‘‹, I'm Mrityunjay Pathak

I'm a Data Scientist with a knack for uncovering patterns and trends that drive smarter decisions.

🎯 Tools and Technologies

β€’ Programming Language : I'm familiar with Python, a powerful language for data science and machine learning.

β€’ Libraries : I'm also familiar with essential data science libraries like NumPy, Pandas, Matplotlib, Seaborn and Plotly.

β€’ Machine Learning : I have experience with Sklearn, a famous machine learning library used widely across industries.

β€’ Database : I can work with MySQL, a popular database management system to handle and retrieve data effectively.

β€’ BI Tools : I'm familiar with Power BI and Excel to perform data analysis, create dynamic dashboards and extract meaningful insights.

β€’ Version Control : I'm familiar with Git, which helps in keeping track of changes in code and collaborating effectively with a team.

πŸ“« Connect with Me

Kaggle  |  LinkedIn  |  GitHub  |  Medium  |  Portfolio

Skills



Projects

Pickify : Movie Recommender System

βž” Problem

  • With the rise of streaming services, viewers now have access to thousands of movies across platforms.
  • As a result, many viewers spend more time browsing than actually watching.
  • This problem can lead to frustration, lower satisfaction and less time spent on the platform.
  • Which can impact both the user experience and business performance.

βž” Solution

  • A content-based movie recommender system built with clean and modular code with proper version control.
  • It analyzes metadata of 5000+ movies to recommend top 5 similar titles based on a user selected input.
  • The system uses techniques like count_vectorizer and cosine_similarity to recommend similar movies.
  • The project not only focuses on functionality but on building a clean and scalable solution.

βž” Impact

If this system gets scaled and integrated with a streaming service, this could :

  • Reduce the time users spend choosing what to watch.
  • Increase user engagement, watch time and customer satisfaction.
  • Help streaming platforms retain users by offering better personalized content.

Link  :  GitHub  |  Application


Netflix Data Analysis

βž” Objective

  • To analyze Netflix content data, uncovering valuable insights into how the platform evolves over time.

βž” 𝗦𝗼𝗺𝗲 π—žπ—²π˜† π—™π—Άπ—»π—±π—Άπ—»π—΄π˜€

  • Cleaned and analyzed dataset of 8000+ Netflix Movies and TV Shows.
  • More than 60% of content on Netflix is rated for mature audiences.
    • Suggests that Netflix targets adult viewers to boost engagement and retention.
  • More than 25% of Movies and TV Shows are released on 1st day of the month.
    • Shows a consistent release schedule, likely to align with subscription cycles.
  • More than 40% of the content on Netflix is exclusive to United States.
    • Shows a strong focus on the U.S. market and content availability by location.
  • More than 20% of the content on Netflix falls under the "Drama" genre.
    • Confirms that "Drama" is a key part of Netflix's content library.
  • More than 23% of the content on Netflix was released in 2019 alone.
    • Indicates a major content push that year, possibly tied to growth or user acquisition goals.

Link  :  GitHub  |  Notebook


Supermarket Sales Analysis

βž” Objective

  • To analyze Supermarket Sales data, identifying key factors for improving profitability and operational efficiency.

βž” 𝗦𝗼𝗺𝗲 π—žπ—²π˜† π—™π—Άπ—»π—±π—Άπ—»π—΄π˜€

  • Analyzed purchasing pattern of 9000+ customers of Supermarket.
  • More than 15% of the products sold were Snacks.
    • Shows that Snacks are a convenient choice and a big source of revenue.
  • More than 32% of the sales were occurred in West region of Supermarket.
    • Suggests that West region is a strong performing area as compared to others.
  • Health and Soft drinks are the most profitable category in Beverages.
    • Shows that both type of drinks option sells well.
  • November was the most profitable month contributing about 15% of the total annual profits.
    • Makes it an ideal time for running promotions and special offers.

Link  :  GitHub  |  Notebook

Certificates

  

Blogs

  

Pinned Loading

  1. Pickify Public

    Pickify : Smart movie picks, based on what you love!

    Jupyter Notebook

  2. TheMrityunjayPathak.github.io Public

    Mrityunjay Pathak

    CSS 1

  3. Netflix-Data-Analysis Public

    Netflix Data Analysis

    Jupyter Notebook

  4. Supermarket-Sales-Analysis Public

    Supermarket Sales Analysis

    Jupyter Notebook