{"product_id":"supervised-machine-learning-with-python-pstrong-develop-rich-python-coding-practices-while-exploring-supervised-machine-learning-p","title":"Supervised Machine Learning with Python","description":"\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDelve into supervised learning and grasp how a machine learns from data\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eImplement popular machine learning algorithms from scratch, developing a deep understanding along the way\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore some of the most popular scientific and mathematical libraries in the Python language\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eSupervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You'll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you'll wrap up with a brief foray into neural networks and transfer learning.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eBy the end of this book, you'll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/h4\u003e\u003cul style=\"margin: 0px 0px 18px 20px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eCrack how a machine learns a concept and generalize its understanding to new data\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUncover the fundamental differences between parametric and non-parametric models\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eImplement and grok several well-known supervised learning algorithms from scratch\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eWork with models in domains such as ecommerce and marketing\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExpand your expertise and use various algorithms such as regression, decision trees, and clustering\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eBuild your own models capable of making predictions\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eDelve into the most popular approaches in deep learning such as transfer learning and neural networks\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/h4\u003e\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eThis book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming―and some fundamental knowledge of supervised learning―are expected.\u003c\/p\u003e\u003ch4 style=\"margin: 0px; padding: 0px 0px 4px; font-family: Arial, sans-serif; text-rendering: optimizelegibility; font-size: 14px;\"\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003c\/h4\u003e\u003col style=\"color: rgb(136, 136, 136); margin-top: 0px; margin-right: 0px; margin-left: 22px; padding-right: 0px; padding-left: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\" margin-bottom:=\"\"\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eFirst step towards supervised learning\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eImplementing parametric models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eWorking with non-parametric models\u003c\/span\u003e\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003e\u003cspan style=\"color:#000000;\"\u003eAdvanced topics in supervised machine learning\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506202972230,"sku":"9781838825669","price":1499.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/smaller_28n8-4n.png?v=1790322958","url":"https:\/\/cb-india.com\/products\/supervised-machine-learning-with-python-pstrong-develop-rich-python-coding-practices-while-exploring-supervised-machine-learning-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}