/CGIAR-Crop-Yield-Prediction-Challenge

code for zindi Competition

Primary LanguageJupyter Notebook

Project on Zindi CGAIR crop Yield Estimation

Usage:

i). Clone the project

git clone https://github.com/RexMudanya/CGIAR-Crop-Yield-Prediction-Challenge.git

ii). Navigate into the project

cd CGIAR-Crop-Yield-Prediction-Challenge/

iii). Install packages

pip install -r requirements.txt

iv). Install jupyter notebooks

pip install notebook

v). Open terminal/command line (cmd) and create a new directory

mkdir data

vi). download from data here and place in data/

vii). Open terminal/command line (cmd) and run

jupyter notebook

viii). Click on relevant notebook, voila!!!

Training the Encoder

  1. To train encoder python train_encoder.py
  2. Launch tensorboard from terminal to visualize logs tensorboard --logdir logs/
  3. Trained encoder saved as encoder.h5

Download data here

Check Leaderboard

Further Discussions