Using #Optuna for hyperparameter optimization to boost model accuracy on the #AirQualityInMadrid dataset. It’s all about finding the right parameters for better predictions! #MachineLearning #HPO #DataScience #Python #DataTalksClub #zoomcamp #Machinelearning
Now training models on the #AirQualityInMadrid dataset! Using LSTM, ARIMA, and other models with #Torch and #Darts. Excited to see how each model performs for time series forecasting. #MachineLearning #TimeSeries #Python #DataTalksClub #zoomcamp #Machinelearning
Data wrangling complete on the #AirQualityInMadrid dataset. Normalized the features, filled missing values, and reshaped the data for time series forecasting. Ready to train some models now! #DataScience #TimeSeries #MachineLearning #Python #DataTalksClub #zoomcamp #Machinelearning
Completing the EDA phase on the #AirQualityInMadrid dataset. Looking for patterns, handling missing values, and investigating the seasonal variations in air quality. EDA is crucial before we move on to model training. #TimeSeries #DataScience #Python #DataTalksClub #zoomcamp #Machinelearning
Task progress: After learning Docker and PostgreSQL, I’m now diving into Terraform for Infrastructure as Code (IaC) in the #Zoomcamp by @DataTalksClub. This task has me automating setups in a whole new way! #Terraform #IaC #DataEngineering #Automation