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Forecasting Wine Sales of Two Different types of Wine. After thorough Data Analysis, different models have been used and tested such as Exponential Smoothing Models, Regression, Naive Forecast, Simple Average, Moving Average. Stationarity of the data is checked. Automated Version of ARIMA/SARIMA Model built. Comparison of Models.

Jupyter Notebook 100.00%
acf-pacf arima-model decomposition exponential-smoothing-models moving-average naive-forecasting prediction regression-models rmse-score sarimax

time-series-forecasting's Introduction

Hi there ๐Ÿ‘‹ I'm Honey.

๐Ÿš€ Data Scientist | AI Enthusiast | Data Enthusiast

  • ๐ŸŽ“ I've successfully completed the Post Graduate Program in Data Science and Business Analytics by Great Learning, in collaboration with McCombs School of Business, UT Austin, Texas.

  • ๐Ÿš€ My passion lies in the realm of Data Science, where I continually explore the breadth and depth of its techniques and tools to extract profound insights from complex datasets.

  • ๐Ÿ” Currently, I'm dedicated to honing my skills across various pillars of Data Science, including Data Analysis, Visualization, Machine Learning, Data Engineering, Deep Learning, and Artificial Intelligence.

  • ๐Ÿ”ญ Engaged in diverse projects, I immerse myself in the realms of Data Analysis, Machine Learning, Data Engineering, and Cloud-based Data Science applications, seeking to unravel patterns and insights from vast and intricate datasets.

  • ๐Ÿ“ซ How to reach me:

  • LinkedIn URL: honey-s-30b71195

  • Feel free to reach out to me via email at [[email protected]].

  • Open to collaboration on exciting projects and initiatives.

๐Ÿ› ๏ธ Data Visualization using Tools and Languages:

SQL Python PowerBI Tableau Knime Pandas NumPy Jupyter Notebook Matplotlib Seaborn scikit-learn Stats

I'm Good at:

  • Data Analysis and Data Mining
  • Data Preprocessing and Cleaning
  • Data Visualization
  • Statistical Analysis
  • Advanced Mathematics
  • Clustering Techniques (Hierarchical Clustering, DBSCAN)
  • Dimensionality Reduction (PCA)
  • Hypothesis Testing
  • Building Machine Learning Models
  • Time Series Analysis
  • Dashboard and KPI Development
  • Business Intelligence Tools (Microsoft Power BI, Tableau)
  • Text Mining
  • A/B Testing
  • Feature Selection and Engineering
  • Model Deployment

Adept at using Tools and Packages:

Linear Regression Logistic Regression Decision Trees Random Forest Support Vector Machine Naive Bayes K-Nearest Neighbors Neural Networks Gradient Boosting Bagging

My Github Stats:

GitHub Streak

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