A Handbook of Mathematical Models with Python: Elevate your machine learning projects with NetworkX, PuLP, and linalg

Введение в книгу : Key benefits Gain a profound understanding of various mathematical models that can be integrated with machine learning Learn how to implement optimization algorithms to tune machine learning models Build optimal solutions for practical use cases Purchase of the print or Kindle book includes a free PDF eBook Description Mathematical modeling is the art of transforming a business problem into a well-defined mathematical formulation. Its emphasis on interpretability is particularly crucial when deploying a model to support high-stake decisions in sensitive sectors like pharmaceuticals and healthcare. Through this book, you’ll gain a firm grasp of the foundational mathematics underpinning various machine learning algorithms. Equipped with this knowledge, you can modify algorithms to suit your business problem. Starting with the basic theory and concepts of mathematical modeling, you’ll explore an array of mathematical tools that will empower you to extract insights and understand the data better, which in turn will aid in making optimal, data-driven decisions. The book allows you to explore mathematical optimization and its wide range of applications, and concludes by highlighting the synergetic value derived from blending mathematical models with machine learning. Ultimately, you’ll be able to apply everything you’ve learned to choose the most fitting methodologies for the business problems you encounter.