This repository contains several beginner-to-intermediate deep learning projects that help build a solid understanding of neural networks, regression, and classification techniques using TensorFlow and Keras.

The goal of this repository is to provide hands-on experience with various deep learning algorithms and real-world datasets. Each project demonstrates the practical implementation of deep learning models — from data preprocessing and model building to evaluation and visualization.

• Objective: Predict whether a customer will churn based on historical data.
• Techniques Used: Artificial Neural Networks (ANN)
• Libraries: TensorFlow, Keras, Pandas, NumPy, Matplotlib
• Outcome: Binary classification model that predicts customer churn probability.

• Objective: Estimate agricultural land prices using regression techniques.
• Techniques Used: Linear Regression, Deep Neural Network (DNN)
• Libraries: TensorFlow, Scikit-learn, NumPy, Pandas
• Outcome: Predicts land prices based on geographical and economic features.

• Objective: Predict house prices using structured real estate data.
• Techniques Used: Linear Regression, ANN
• Libraries: TensorFlow, Keras, Scikit-learn
• Outcome: Model that outputs predicted house prices with improved accuracy through deep learning.

• Languages: Python 🐍
• Libraries: TensorFlow, Keras, NumPy, Pandas, Scikit-learn, Matplotlib
• Environment: Jupyter Notebook (.ipynb files)

git clone https://github.com/ritirai06/Basic-Deep-Learning-Projects.git
cd Basic-Deep-Learning-Projects

pip install -r requirements.txt

Open any .ipynb file using Jupyter Notebook or VS Code and execute the cells step by step.

• Improved understanding of deep learning basics such as ANN, regression, and classification.
• Hands-on implementation of TensorFlow & Keras models.
• Learning how to handle real-world datasets for predictive modeling.

• Add CNN and RNN projects for image and text data.
• Implement model optimization and hyperparameter tuning.
• Include visualization dashboards for predictions.

Riti Rai 🎓 Data Science & AI Enthusiast | 💡 Exploring Deep Learning and NLP 📧 Connect on GitHub

Deep Learning • TensorFlow • Keras • Regression Models • Neural Networks • Classification