{"product_id":"advanced-forecasting-with-python-9798868820274","title":"Advanced Forecasting with Python","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp class=\"MsoNormal\"\u003ePART I: Machine Learning for Forecasting.- Chapter 1: Models for Forecasting.- Chapter 2: Model Evaluation for Forecasting.- Chapter 3: Model Management and Benchmarking using MLflow.- PART II: Univariate Time Series Models.- Chapter 4: The AR model.- Chapter 5: The MA model.- Chapter 6: The ARMA model.- Chapter 7: The ARIMA model.- Chapter 8: The SARIMA model.- PART III: Multivariate Time Series Models.- Chapter 9: The SARIMAX model.- Chapter 10: The VAR model.- Chapter 11: The VARMAX model.- PART IV: Supervised Models.- Chapter 12: The Linear Regression.- Chapter 13: The Decision Tree Model.- Chapter 14: The kNN model.- Chapter 15: The Random Forest.- Chapter 16: Gradient Boosting with XGBoost, LightGBM, and CatBoost.- Chapter 17: Bayesian Models with pyBATS.- PART V: Neural Networks.- Chapter 18: Neural Networks.- Chapter 19: RNNs using SimpleRNN and GRU.- Chapter 20: LSTM RNNs.- PART VI: Black Box and Cloud Based Models.- Chapter 21: The NBEATS model with Darts.- Chapter 22: The Transformer model with Darts.- Chapter 23: The NeuralProphet model.- Chapter 24: The DeepAR model and AWS Sagemaker AI.- Chapter 25: Uber's Orbit Model.- Chapter 26: AutoML with Microsoft Azure.- Chapter 27: AutoML with Vertex AI on Google Cloud Platform.- Chapter 28: Nixtla Suite and TimeGPT.- Chapter 29: Model Selection.\u003c\/p\u003e","brand":"Apress","offers":[{"title":"Default Title","offer_id":53239305404759,"sku":"9798868820274","price":37.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/advanced-forecasting-with-python-9798868820274","provider":"Book Curl","version":"1.0","type":"link"}