Time Series Forecasting
Keras
English
time-series
stock-forecasting
LSTM
ARIMA
Prophet
machine-learning
deep-learning
forecasting
Instructions to use Hiruni2207/DataSynthis_ML_JobTask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Hiruni2207/DataSynthis_ML_JobTask with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Hiruni2207/DataSynthis_ML_JobTask") - Notebooks
- Google Colab
- Kaggle
Upload performance_summary.csv with huggingface_hub
Browse files- performance_summary.csv +4 -0
performance_summary.csv
ADDED
|
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Model,RMSE,MAPE
|
| 2 |
+
ARIMA,3.3747959050510263,1.89735011501022
|
| 3 |
+
Prophet,4.7650432414652215,3.1859116338570725
|
| 4 |
+
LSTM,2.0890386404819212,1.2515893580288606
|