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Repository containing portfolio of data science projects completed for self learning and professional purposes. Presented in the form of Jupyter Notebooks.

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Data-Science--Project and Code

Repository containing portfolio of data science projects completed for self learning and professional purposes. Presented in the form of Jupyter Notebooks.

Tools:

  • Python: NumPy, Pandas, Seaborn, Matplotlib
  • Machine Learning: Scikit-learn, TensorFlow, Keras
  • Time Series : Statsmodel, pmdarima, TensorFlow, Keras
  • NLP : NLTK, TensorFlow, Keras

Contents

Machine Learning

Forecasting

  • Weekly Fuel Price Forecasting
    • Create a forecasting model to forecast weekly petrol and diesel prices using a combination of forecasting and regression methods. The fluctuations are often unpredictable, so this method can adjust for changes.
  • Netflix Stock Price Forecasting
    • Forecasting model to predict the Netflix closing stock price using the forecasting methods, with exogenous variables. This model focus to predict the daily closing price, it can help for daily trading.
  • Google Stock Price Forecasting LSTM
    • Forecast the Google stock price using LSTM model

NLP

  • Yelp Sentiment Analysis
    • Analyze and visualize sentiment from customer reviews on Yelp data. We can find out what businesses are popular and how customers respond to their experiences.
  • Text Emotion Classification using LSTM
    • Predict emotions (joy, sadness, anger, fear, love, and surprise) from text using LSTM model

Data Analysis

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Repository containing portfolio of data science projects completed for self learning and professional purposes. Presented in the form of Jupyter Notebooks.

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