hanahh080601/Basic-Deep-Learning-Exercise

Basic-Deep-Learning-Exercise

Build a basic Neural Network using pure Numpy and Pandas.

Tasks

• Preprocessing data
  • Loading data
  • Transform data
  • Split data
• Building model
  • Initialize weights & biases
  • Activation function
  • Loss function
  • Feed forward
  • Backpropagation
  • Update weights
• Training
  • • Execute (train, validate, test).
• Evaluating
  • Accuracy: approx 80 - 83%

Installation

Clone the repo from Github and pull the project.

git clone https://github.com/hanahh080601/Basic-Deep-Learning-Exercise.git
git checkout hanlhn/multi-layers-nn
git pull
cd hanlhn/hanlhn
poetry install
poetry config virtualenvs.in-project true
poetry update

Project tree

.
├── hanlhn
│ ├── .venv
│ ├── poetry.lock
│ ├── pyproject.toml
│ ├── README.rst
│ └── hanlhn
│ ├── pycache
│ ├── data
│ │ ├── dataset │ │ │ ├── test_record.csv
│ │ │ └── train_record.csv
│ │ └── datapipeline.py
│ ├── models
│ │ ├── TwoLayersNN.py
│ │ ├── FCL.py
│ │ └── MultiLayersNN.py
│ ├── tests
│ │ ├── init.py
│ │ └── test_hanlhn.py
│ ├── init.py
│ ├── config.py
│ └── main.py
├── .gitignore
└── README.md

Usage:

cd hanlhn/hanlhn
python main.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

Author

Lê Hoàng Ngọc Hân - Đại học Bách Khoa - Đại học Đà Nẵng (DUT)