All the ML projects done using the uber's LUDWIG
What is Ludwig ?
Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
For All instructions about the installation you can refer: https://uber.github.io/ludwig/getting_started/
All Examples of the commands and input files will be passed to ludwig
Model Definition: {input_features: [{name: content, type: text}], output_features: [{name: airline_sentiment, type: category}]}
Ludwig Train: ludwig train --data_csv ./Tweets.csv --model_definition "{input_features: [{name: content, type: text}], output_features: [{name: airline_sentiment, type: category}]}"
Ludwig Visualize: ludwig visualize --visualization learning_curves --training_statistics ./Tweets.json
Ludwig Predict: ludwig predict --data_csv path/to/data.csv --model_path /path/to/model
Ludwig Visualize: ludwig visualize --visualization compare_performance --test_statistics path/to/test_statistics_model_1.json path/to/test_statistics_model_2.json
Available datatypes in Ludwig:
binary
numerical
category
set
bag
sequence
text
timeseries
image