Hands-On Recommendation Systems with Python: Start building powerful and persona

Description: Hands-On Recommendation Systems with Python by Rounak Banik Recommendation systems are at the heart of almost every internet business today; from Facebook to Netflix to Amazon. Providing good recommendations, whether its friends, movies or groceries, goes a long way in defining user experience and enticing your customers to use and buy from your platform. This book teaches you to do just that. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the webKey FeaturesBuild industry-standard recommender systemsOnly familiarity with Python is requiredNo need to wade through complicated machine learning theory to use this bookBook DescriptionRecommendation systems are at the heart of almost every internet business today; from Facebook to Netix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform.This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory—youll get started with building and learning about recommenders as quickly as possible..In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. Youll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time youre fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains.What you will learnGet to grips with the different kinds of recommender systemsMaster data-wrangling techniques using the pandas libraryBuilding an IMDB Top 250 CloneBuild a content based engine to recommend movies based on movie metadataEmploy data-mining techniques used in building recommendersBuild industry-standard collaborative filters using powerful algorithmsBuilding Hybrid Recommenders that incorporate content based and collaborative flteringWho this book is forIf you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory. Author Biography Rounak Banik is a Young India Fellow and an ECE graduate from IIT Roorkee. He has worked as a software engineer at Parceed, a New York start-up, and Springboard, an EdTech start-up based in San Francisco and Bangalore. He has also served as a backend development instructor at Acadview, teaching Python and Django to around 35 college students from Delhi and Dehradun. He is an alumni of Springboards data science career track. He has given talks at the SciPy India Conference and published popular tutorials on Kaggle and DataCamp. Table of Contents Table of ContentsGetting Started with Recommender SystemsManipulating Data with the Pandas LibraryBuilding an IMDB Top 250 Clone with PandasBuilding Content-Based RecommendersGetting Started with Data Mining TechniquesBuilding Collaborative FiltersHybrid Recommenders Long Description With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features Build industry-standard recommender systems Only familiarity with Python is required No need to wade through complicated machine learning theory to use this book Book Description Recommendation systems are at the heart of almost every internet business today; from Facebook to Netix to Amazon. Providing good recommendations, whether its friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory--youll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. Youll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time youre fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. What you will learn Get to grips with the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content based engine to recommend movies based on movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative fltering Who this book is for If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory. Details ISBN1788993756 Author Rounak Banik Pages 146 Publisher Packt Publishing Limited Year 2018 ISBN-10 1788993756 ISBN-13 9781788993753 Format Paperback Publication Date 2018-07-31 Short Title Hands-On Recommendation Systems with Python Language English UK Release Date 2018-07-31 Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom AU Release Date 2018-07-31 NZ Release Date 2018-07-31 Subtitle Start building powerful and personalized, recommendation engines with Python DEWEY 006.331 Audience General We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:118834215;

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