Cracking The Machine Learning Code Technicality Or Innovation
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Cracking the Machine Learning Code: Technicality or Innovation?
Employing off-the-shelf machine learning models is not an innovation. The journey through technicalities and innovation in the machine learning field is ongoing, and we hope this book serves as a compass, guiding the readers through the evolving landscape of artificial intelligence. It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability. Innovation in building machine learning models involves a continuous cycle of exploration, experimentation, and improvement, with a focus on pushing the boundaries of what is achievable while considering ethical implications and real-world applicability. The book is aimed at providing a clear guidance that one should not be limited to building pre-trained models to solve problems using the off-the-self basic building blocks. With primarily three different data types: numerical, textual, and image data, we offer practical applications such as predictive analysis for finance and housing, text mining from media/news, and abnormality screening for medical imaging informatics. To facilitate comprehension and reproducibility, authors offer GitHub source code encompassing fundamental components and advanced machine learning tools.
Cracking the Machine Learning Code: Technicality or Innovation?
Employing off-the-shelf machine learning models is not an innovation. The journey through technicalities and innovation in the machine learning field is ongoing, and we hope this book serves as a compass, guiding the readers through the evolving landscape of artificial intelligence. It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability. Innovation in building machine learning models involves a continuous cycle of exploration, experimentation, and improvement, with a focus on pushing the boundaries of what is achievable while considering ethical implications and real-world applicability. The book is aimed at providing a clear guidance that one should not be limited to building pre-trained models to solve problems using the off-the-self basic building blocks. With primarily three different data types: numerical, textual, and image data, we offer practical applications such as predictive analysis for finance and housing, text mining from media/news, and abnormality screening for medical imaging informatics. To facilitate comprehension and reproducibility, authors offer GitHub source code encompassing fundamental components and advanced machine learning tools.
Cracking the Innovation Code
Author Dr Andy Wynn, along with contributions from leaders of some of the biggest companies on the planet (including DuPont, 3M, Johnson Matthey and Imerys), finally reveals the secret of how you can unlock the potential in your business to grow. In the follow up to his book Transforming Technology into Profit, Andy takes you on a journey that explains how the organisation and culture within your business impact your company’s ability to innovate. Using his "Three Tiers of Successful Innovation", Andy reveals how to clearly identify what aspects of your business are holding back growth and how to use that information to transform your business into one that facilitates growth by revitalising the structure and culture of your business to focus employee behaviours on adding profitable new revenue streams. Part sequel and part companion volume to his previous book, Andy finally "cracks the code" on how to unleash your business’ ability to create and successfully commercialise new products. Written in the author’s trademark conversational style, Cracking the Innovation Code offers a refreshingly practical and real-world view, written by someone who has been there and done it, and enhanced by valuable case studies and contributions from numerous senior executives who have made life-long careers out of leading innovation, and with a passion for leading industrial manufacturing businesses.