{"product_id":"python-machine-learning-cookbook-2-e-pstrong-over-100-recipes-to-progress-from-smart-data-analytics-to-deep-learning-using-real-world-datasets-p","title":"Python Machine Learning Cookbook, 2\/E","description":"\u003cp style=\"margin: 0px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003e\u003cb\u003eDiscover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch\u003c\/b\u003e\u003c\/p\u003e\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;\"\u003eLearn and implement machine learning algorithms in a variety of real-life scenarios\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eCover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eFind easy-to-follow code solutions for tackling common and not-so-common challenges\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:=\"\"\u003eThis eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks.\u003c\/p\u003e\u003cp style=\"margin: -4px 0px 14px; padding: 0px; font-family: \" amazon ember arial sans-serif font-size:=\"\"\u003eWith the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine 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 will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples.\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;\"\u003eUse predictive modeling and apply it to real-world problems\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eExplore data visualization techniques to interact with your data\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eLearn how to build a recommendation engine\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUnderstand how to interact with text data and build models to analyze it\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eWork with speech data and recognize spoken words using Hidden Markov Models\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eGet well versed with reinforcement learning, automated ML, and transfer learning\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eWork with image data and build systems for image recognition and biometric face recognition\u003c\/li\u003e\n\u003cli style=\"margin: 0px 0px 0px 20px; overflow-wrap: break-word;\"\u003eUse deep neural networks to build an optical character recognition system\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 data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful.\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;\"\u003eThe Realm of Supervised Learning\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eConstructing a Classifier\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003ePredictive Modeling\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eClustering with Unsupervised Learning\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eVisualizing Data\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eBuilding Recommendation Engines\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eAnalyzing Text Data\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eSpeech Recognition\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eDissecting Time Series and Sequential Data\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eImage Content Analysis\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eBiometric Face Recognition\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eReinforcement Learning Techniques\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eDeep Neural Networks\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eUnsupervised Representation Learning\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eAutomated machine learning and Transfer learning\u003c\/li\u003e\n\u003cli style=\"margin: 0px; overflow-wrap: break-word;\"\u003eUnlocking Production issues\u003c\/li\u003e\n\u003c\/ol\u003e","brand":"Packt Publishing","offers":[{"title":"Default Title","offer_id":50506194288710,"sku":"9781789808452","price":2174.25,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0754\/2797\/1142\/files\/smaller_bn21-jr.png?v=1790322645","url":"https:\/\/cb-india.com\/products\/python-machine-learning-cookbook-2-e-pstrong-over-100-recipes-to-progress-from-smart-data-analytics-to-deep-learning-using-real-world-datasets-p","provider":"Computer Bookshop (India) Pvt Ltd","version":"1.0","type":"link"}