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ranam4998/README.md
  • ๐Ÿ‘‹ Hi, Iโ€™m Manish Rana!
  • ๐Ÿ” Passionate about uncovering insights and telling stories with data. I have experience in data cleaning, data visualization, and statistical analysis, using Python, and SQL.
  • ๐Ÿ“Š Skilled in working with tools like Pandas, NumPy, Matplotlib, Seaborn, and Tableau.
  • ๐Ÿ“ˆ Currently pursuing a certification course in Data Science to enhance my expertise in machine learning, time series analysis, and big data.
  • ๐Ÿ’ก I love tackling complex problems and am always looking to expand my knowledge.
  • ๐Ÿ‘€ Iโ€™m interested in uncovering insights from data, exploring patterns, and creating impactful visualizations that tell a story. Iโ€™m also passionate about machine learning and predictive analytics.
  • ๐ŸŒฑ Iโ€™m currently learning advanced techniques in data science, including machine learning algorithms, time series analysis, and big data processing.
  • ๐Ÿ’ž๏ธ Iโ€™m looking to collaborate on data analysis projects, especially those involving Python, SQL, data visualization, and predictive modeling.
  • ๐Ÿ“ซ How to reach me: ranam4998@gmail.com or connect with me on LinkedIn https://www.linkedin.com/in/manish-rana-037329335.
  • โšก Fun fact: I enjoy exploring new data visualization tools and techniques, and Iโ€™m always up for a good data challenge!

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  1. Machine-Learning Machine-Learning Public

    Examine Data | Build Framework | Evaluating and Comparing regression Models

    Jupyter Notebook

  2. Mall-Customer-Segmentation-Unsupervised_ML- Mall-Customer-Segmentation-Unsupervised_ML- Public

    The Goal is to segment customers based in their behaviors and attributes, providing valuable insights for marketing strategies. Although customer segmentation is a typical application clustering, tโ€ฆ

    Jupyter Notebook

  3. ML_Project ML_Project Public

    Python

  4. Cognifyz_Technologies Cognifyz_Technologies Public

    Top Cuisines | City Analysis | Price Range Distribution | Online Delivery | Restaurant Ratings | Cuisine Combination | Geographical Analysis | Restaurant Chains

    Jupyter Notebook