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TimesNet: The Latest Advance in Time Series Forecasting
Towards Data Science
In this article, we explore the architecture and inner workings of TimesNet. Then, we apply the model in a forecasting task, alongside N-BEATS and N-HiTS.
11 months ago
A review of machine learning concepts and methods for addressing challenges in probabilistic hydrological post-processing and forecasting
Frontiers
Probabilistic forecasting is receiving growing attention nowadays in a variety of applied fields, including hydrology. Several machine learning concepts and...
14 months ago
Global deep learning for joint time series forecasting
Towards Data Science
A predictive model is called global when it is trained on many different datasets, each being the random outcome of its own stochastic process.
25 months ago
A holistic and proactive approach to forecasting cyber threats
Nature
This paper introduces a novel ML-based approach that leverages unstructured big data and logs to forecast the trend of cyber-attacks at a large scale, years in...
15 months ago
12 Data Science Projects for Beginners and Experts
Built In
Data science is a booming industry that involves extracting information, analyzing it and putting it to use. Try your hand at these projects to develop your...
21 months ago
(PDF) Impact of Hyperparameter Tuning on Machine Learning Models in Stock Price Forecasting
ResearchGate
PDF | Stock price forecasting has been reported as a challenging task in the scientific and financial communities due to stock prices' nonlinear and.
31 months ago
Comprehensive assessment, review, and comparison of AI models for solar irradiance prediction based on different time/estimation intervals
Nature
Solar energy-based technologies have developed rapidly in recent years, however, the inability to appropriately estimate solar energy...
27 months ago
Time-Series Forecasting: Deep Learning vs Statistics — Who Wins?
Towards Data Science
Time series, also sequential in nature, raise the question: what happens if we bring the full power of pretrained transformers to...
17 months ago
(PDF) Meta-analysis using Python: a hands-on tutorial
ResearchGate
PDF | Background Meta-analysis is a central method for quality evidence generation. In particular, meta-analysis is gaining speedy momentum...
26 months ago
Using machine learning methods to predict electric vehicles penetration in the automotive market
Nature
The main goal of this research is to apply Machine Learning (ML) methods to build an efficient prediction model to estimate the sale of all vehicles in the...
15 months ago