Tabular Regression
Keras
Joblib
English
battery
state-of-health
remaining-useful-life
time-series
regression
lstm
transformer
xgboost
lightgbm
random-forest
ensemble
Instructions to use NeerajCodz/aiBatteryLifeCycle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use NeerajCodz/aiBatteryLifeCycle with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://NeerajCodz/aiBatteryLifeCycle") - Notebooks
- Google Colab
- Kaggle
File size: 126 Bytes
c8de822 | 1 2 3 4 5 6 | {
"xgboost": 0.4115706608011118,
"random_forest": 0.5247830956665503,
"extra_trees": 0.0,
"tft": 0.06364624353233779
} |