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Some Gaps in Machine Learning by editor.ijcrsetjournals is a document available to read on EtoBox.

The editorial discusses the complexities and gaps in Machine Learning, emphasizing its relationship with mathematics, science, and technology. It critiques the current results-oriented paradigm that prioritizes outcomes over explainability and interpretability, highlighting the challenges in formulating hypotheses based on Machine Learning algorithms. The author advocates for a focus on explainability and interpretability to enhance understanding and application of Machine Learning methods.

Author
editor.ijcrsetjournals
Language
EN