Feature Engineering Made Easy: Identify unique features from your dataset in order to build powerful machine learning systems by Sinan Ozdemir, Divya Susarla
English | March 15th, 2018 | ISBN: 1787287602 | 316 Pages | EPUB | 5.51 MB
Feature engineering is essential to applied machine learning, but using domain knowledge to strengthen your predictive models can be difficult and expensive.
Statistics for Engineering and the Sciences, Sixth Edition is designed for a two-semester introductory course on statistics for students majoring in engineering or any of the physical sciences. This popular text continues to teach students the basic concepts of data description and statistical inference as well as the statistical methods necessary for real-world applications. Students will understand how to collect and analyze data and think critically about the results.
For courses in engineering and economics Comprehensively blends engineering concepts with economic theory Contemporary Engineering Economics teaches engineers how to make smart financial decisions in an effort to create economical products.
If you have designs for wonderful machines in mind, but aren’t sure how to turn your ideas into real, engineered products that can be manufactured, marketed, and used, this book is for you. Engineering professor and veteran maker Tom Ask helps you integrate mechanical engineering concepts into your creative design process by presenting them in a rigorous but largely nonmathematical format.
Engineering Economy presents a crisp, bold new design using color, highlighting and icons to focus on important concepts, terms, equations and decision guidelines. There are new features, new topics (such as ethics and staged decision making), and new online tools; yet no compromise on coverage, examples, or the well-accepted writing style of this popular text. Solved examples, problems and case studies target many of the current engineering challenges in areas such as energy, ethics, the environment, and the world’s changing economics.