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  • Deep learning in cancer diagnostics : a feature-based transfer learning evaluation

    • Authors: Mohd Hafiz Arzmi (2023)

  • In this brief, the diagnosis of four types of common cancers, i.e., breast, lung, oral and skin, are evaluated with different state-of-the-art feature-based transfer learning models. It is expected that the findings in this book are insightful to various stakeholders in the diagnosis of cancer
  • Sách/Book

  • Time Series Algorithms Recipes Implement Machine Learning and Deep Learning Techniques with Python

    • Authors: Akshay R. Kulkarni (2023)

  • This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average).