Machine-Learning 🧠

A repository of machine learning experiments, data analysis projects, and predictive modeling notebooks by Rohit R (rohitr534).

---

📂 Contents

File / Notebook	Description
All_data.csv	Combined dataset used across various notebooks.
Amex final.ipynb	Final model & analysis for AMEX dataset.
Optimization of Data Compression.pdf	A write-up on compressing data / feature reduction techniques.
Stat collider simulation.ipynb	Statistical simulation to explore collider bias.
imc-sub.ipynb	Prediction or classification project (IMC subject / dataset).
leapsub2.ipynb	An experiment comparing feature selection / “leap” methods.
prediction-using-ridge-lasso-linear.ipynb	Comparing linear, Ridge & Lasso regression models for prediction.
sales.ipynb	Forecasting / analysis project around sales data.
stock-price-best(1).ipynb	Stock price prediction experiment.

---

🎯 Objective

• To build and refine machine learning models for real-world datasets.
• To explore different modeling approaches: regression, regularization (Ridge, Lasso), simulation, feature selection, etc.
• To enhance understanding of statistical phenomena (e.g. collider bias) and data processing techniques (feature engineering, dimensionality reduction).

---

🛠️ Tools & Technology Stack

Category	Tools / Libraries
Language / Environment	Python, Jupyter Notebooks
Data Manipulation & Visualization	Pandas, NumPy, Matplotlib / Seaborn
Modeling	Scikit-learn, (Optionally: statsmodels, etc.)
Others	PDF / documentation (for write-ups), data preprocessing, feature selection

---

🚀 How to Run / Use

1. Clone this repo

   git clone https://github.com/rohitr534/Machine-Learning.git
   cd Machine-Learning