ML Predictive Models 🧠📊

A collection of machine learning projects focused on solving real-world problems using classification, regression, and NLP techniques. These are personal projects originally done for experimentation, now cleaned and restructured.

---

📁 Projects Included

🔍 1. Customer Churn Prediction

Predicts whether a customer will leave a telecom company using logistic regression and decision trees.
Tech Used: Pandas, Scikit-learn, Matplotlib

🧾 2. SMS Spam Detector

Classifies SMS messages as spam or ham using NLP and Naive Bayes.
Tech Used: NLTK, Scikit-learn, TfidfVectorizer

🎬 3. Movie Genre Classifier

Predicts movie genres based on text features using multi-label classification.
Tech Used: Scikit-learn, NLP, MultiOutputClassifier

💳 4. Credit Card Fraud Detection

Detects fraudulent transactions using anomaly detection methods.
Tech Used: Isolation Forest, PCA, Logistic Regression

---

🚀 How to Run

1. Clone the repository:

   git clone https://github.com/Shwetraj1/ml-predictive-models.git

2. Install dependencies:

   pip install -r requirements.txt

3. Open each .ipynb file in Jupyter or VS Code and run the cells.

💡 Why This Repo Exists

These aren’t tutorial copies — they’re stepping stones in my ML journey. I’m a builder, not a course collector. Every project here taught me how to move from theory to tool — and now they serve as reference points for bigger AI systems like ShadowGPT.

🧠 Tech Stack

Python

Scikit-learn

Pandas, NumPy, Matplotlib

NLTK / NLP

Jupyter Notebooks

📬 Contact

Built by Shwet Raj — engineering student, AAI intern, and AI toolsmith.

Let’s connect if you want to collaborate on AI, digital infrastructure, or productivity tools.