/Financial_Analysis_Using_Python_and_ML_Libraries

This repository has been created as part of my Udemy Course learning "Python & Machine Learning for Financial Analysis" by Dr. Ryan Ahmed.

Primary LanguageJupyter Notebook

Financial_Analysis_Using_Python_and_ML_Libraries

🔬 Description

  • This series of collab notebooks deals with Financial Analysis using Python and Machine Learning Libraries.
  • This repository has been created as part of my Udemy Course learning "Python & Machine Learning for Financial Analysis" by Dr.Ryan Ahmed.
  • The notebook files are some of the hands-on projects designed to harness the power of Data science and AI to optimize business processes, maximize revenue, reduce costs.

Link to Course ➡️ Udemy

💡 Key Learnings

  • Applied Python 3 fundamentals in Data Science and Machine Learning, with a focus on Finance.
  • Leveraged Python for financial computations such as portfolio returns, risk and Sharpe ratio calculations.
  • Built, trained, and tuned Machine Learning models with SciKit-Learn on real-world datasets, including application in banking and finance sectors for tasks such as stock price prediction, fraud detection, and customer segmentation.
  • Gained insights into various Machine Learning algorithms for regression, classification and clustering tasks, and learned how to assess their performance using appropriate KPIs.
  • Explored the theory and application of Artificial Neural Networks (ANNs), Recurrent Neural Networks (RNNs), and Long Short Term Memory Networks (LSTM), and learned to optimize ANNs' hyperparameters for improved performance.
  • Developed strong skills in feature engineering and data cleaning for Machine Learning and Data Science applications.

💻 Libraries Used

Matplotlib NumPy Pandas Plotly SciPy scikit-learn TensorFlow

😎 Projects

📖 Datasets Used

https://drive.google.com/file/d/10KwseRQO8Qne7YXS6OLAgDSJ9codqPyq/view?usp=sharing🔗

https://drive.google.com/file/d/1OLwQTbt3HvT8YaKNy2wlYeYBzpnoy09Y/view?usp=sharing 🔗

https://drive.google.com/file/d/1lPZZpxOQ-Hv3690VscbgAmUrXyFVhQhA/view?usp=sharing 🔗

1️⃣ Data Analysis and Visualization of Stock Data

https://github.com/ManikantaSanjay/Financial_Analysis_Using_Python_and_ML_Libraries/blob/main/Stocks_Data_Analysis_and_Visualization.ipynb 🔗

2️⃣ Portfolio Assets Allocation and Statistical Data Analysis of Stock Data

https://github.com/ManikantaSanjay/Financial_Analysis_Using_Python_and_ML_Libraries/blob/main/Portfolio_Assets_Allocation_and_Statistical_Data_Analysis.ipynb 🔗

3️⃣ Capital Asset Pricing Model (CAPM) of Stocks

https://github.com/ManikantaSanjay/Financial_Analysis_Using_Python_and_ML_Libraries/blob/main/Capital_Asset_Pricing_Model_(CAPM).ipynb 🔗

4️⃣ Stock Price Prediction Using Ridge Regression Model and LSTMs

https://github.com/ManikantaSanjay/Financial_Analysis_Using_Python_and_ML_Libraries/blob/main/Stock_Price_Predictions_Using_Ridge_regression_%26_LSTM.ipynb 🔗

5️⃣ Sentiment Analysis of Twitter Data for Company Stocks using Deep Neural Networks and LSTMs

https://github.com/ManikantaSanjay/Financial_Analysis_Using_Python_and_ML_Libraries/blob/main/Sentiment_Analysis_from_Tweets.ipynb 🔗

🙇 Special Thanks

Dr. Ryan Ahmed for the amazing coursework.