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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).
  • Sách/Book

  • Curriculum Design and Development

    • Authors: DR.C.THANAVATHI (2017)

  • This book is a synthesis of extensive collection of curriculum. This book is thus intended to make a contribution not only to the field of curriculum but also covers all the categories of curriculum development. This book seeks to describe and examine the processes of curriculum development and teachers-in-training with fundamental issues and practices in curriculum development. The book tries to provide as many examples as possible of how some of the practical problems in curriculum development have been addressed by practitioners in many parts of the world.