This project explores deep learning techniques to solve complex problems such as image recognition, NLP, and predictive modeling. It demonstrates building, training, and evaluating neural networks using popular deep learning frameworks.
- Data preprocessing and cleaning
- Exploratory data analysis (EDA)
- Implementation of deep learning models:
- CNNs for image tasks
- RNNs / LSTMs for sequence tasks
- Model training, evaluation, and tuning
- Visualization of training metrics and results
- Python 3.10+
- Libraries:
TensorFlow/Keras– Neural networksPyTorch– Deep learning frameworknumpy– Numerical computationspandas– Data manipulationmatplotlib/seaborn– Visualization- Jupyter Notebook