What are the main challenges encountered during the data preprocessing step in machine learning, and how can addressing these challenges improve the effectiveness of a model?
Saturday, 26 April 2025 by Mohammed Khaled
The data preprocessing step in machine learning is a critical phase that significantly impacts the performance and effectiveness of a model. It involves transforming raw data into a clean and usable format, ensuring that the machine learning algorithms can process the data effectively. Addressing the challenges encountered during this step can lead to improved model
Is it necessary to use other data for training and evaluation of the model?
Monday, 13 November 2023 by Hema Gunasekaran
In the field of machine learning, the use of additional data for training and evaluation of models is indeed necessary. While it is possible to train and evaluate models using a single dataset, the inclusion of other data can greatly enhance the performance and generalization capabilities of the model. This is especially true in the
- Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Introduction, What is machine learning
Tagged under: Artificial Intelligence, Concept Drift, Data Augmentation, Data Imbalance, Generalization, Overfitting