Python For Marketing Research And Analytics

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Python for Marketing Research and Analytics

Author : Jason S. Schwarz
Publisher : Springer Nature
ISBN 13 : 3030497208
Total Pages : 272 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Python for Marketing Research and Analytics by : Jason S. Schwarz

Download or read book Python for Marketing Research and Analytics written by Jason S. Schwarz and published by Springer Nature. This book was released on 2020-11-03 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas. Following the Python scientific computing movement toward reproducible research, the book presents all analyses in Colab notebooks, which integrate code, figures, tables, and annotation in a single file. The code notebooks for each chapter may be copied, adapted, and reused in one's own analyses. The book also introduces the usage of machine learning predictive models using the Python sklearn package in the context of marketing research. This book is designed for three groups of readers: experienced marketing researchers who wish to learn to program in Python, coming from tools and languages such as R, SAS, or SPSS; analysts or students who already program in Python and wish to learn about marketing applications; and undergraduate or graduate marketing students with little or no programming background. It presumes only an introductory level of familiarity with formal statistics and contains a minimum of mathematics.

R for Marketing Research and Analytics

Author : Chris Chapman
Publisher : Springer
ISBN 13 : 3319144367
Total Pages : 454 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis R for Marketing Research and Analytics by : Chris Chapman

Download or read book R for Marketing Research and Analytics written by Chris Chapman and published by Springer. This book was released on 2015-03-09 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

Data Science for Marketing Analytics

Author : Tommy Blanchard
Publisher : Packt Publishing Ltd
ISBN 13 : 1789952107
Total Pages : 420 pages
Book Rating : 4.7/5 (899 download)

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Book Synopsis Data Science for Marketing Analytics by : Tommy Blanchard

Download or read book Data Science for Marketing Analytics written by Tommy Blanchard and published by Packt Publishing Ltd. This book was released on 2019-03-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.

Marketing Data Science

Author : Thomas W. Miller
Publisher : FT Press
ISBN 13 : 0133887340
Total Pages : 810 pages
Book Rating : 4.1/5 (338 download)

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Book Synopsis Marketing Data Science by : Thomas W. Miller

Download or read book Marketing Data Science written by Thomas W. Miller and published by FT Press. This book was released on 2015-05-02 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Marketing Analytics

Author : Wayne L. Winston
Publisher : John Wiley & Sons
ISBN 13 : 1118417305
Total Pages : 727 pages
Book Rating : 4.1/5 (184 download)

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Book Synopsis Marketing Analytics by : Wayne L. Winston

Download or read book Marketing Analytics written by Wayne L. Winston and published by John Wiley & Sons. This book was released on 2014-01-08 with total page 727 pages. Available in PDF, EPUB and Kindle. Book excerpt: Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel.

Data Science for Marketing Analytics

Author : Mirza Rahim Baig
Publisher : Packt Publishing Ltd
ISBN 13 : 1800563884
Total Pages : 637 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Data Science for Marketing Analytics by : Mirza Rahim Baig

Download or read book Data Science for Marketing Analytics written by Mirza Rahim Baig and published by Packt Publishing Ltd. This book was released on 2021-09-07 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

Data Analysis for Social Science and Marketing Research Using Python

Author : Manoj Morais
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781533213839
Total Pages : 264 pages
Book Rating : 4.2/5 (138 download)

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Book Synopsis Data Analysis for Social Science and Marketing Research Using Python by : Manoj Morais

Download or read book Data Analysis for Social Science and Marketing Research Using Python written by Manoj Morais and published by Createspace Independent Publishing Platform. This book was released on 2016-05-22 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is written for researchers in social science and marketing field, especially for those with little or no knowledge in computer programming. Data analytics has become part and parcel in the contemporary technologically fast paced world. We have amazing tools and software that allow us to analyse data available in various formats. However, most of the popular paid software and packages for data analysis is not affordable or not even accessible for the students, researchers. This is true in the case of many NGOs and agencies how are involved in community based research in developing countries. We have popular open source platforms and tools such as R and Python for data analysis. This book makes use of Python because of its simplicity, adaptability, broader scope and greater potential in advanced data mining and text mining contexts. We found it as a need to educate and train the researchers from social science and marketing research background, so that they could make use of Python, a promising tool to meet simple to extremely complex data analyses needs free of cost. The learnings from this book will not only help them in doing their conventional data analyses but also enable them to pursue advanced knowledge in machine learning algorithms, text analytics and other new generation techniques with the support of freely accessible open source platforms. Since the objective of the book is to educate the researchers with no programming background, we have made every effort to give hands-on experience in learning some basic coding in Python, which is sufficient for the readers to follow the book. The step-by-step procedure to do various data processing and analysis described in this book will make it easy for the users. Apart from that, we have tried our level best to give explanations on specific codes and how they perform to get us the desired output. We also request you to give you valuable comments and suggestions on the book, via our blog, so that we could improve the same in the upcoming volumes. We commit ourselves to providing explanations to the readers' questions related to the codes and analysis provided in this book. The book specifically deals with data sets of row and column format, as the general format commonly used in social science research, which most of the researchers are familiar with. So we do not work with arrays and dictionaries, except in one or two occasions (only to make you familiar with that) instead prefer to make use of Excel data and pandas data frame. The book consists of thirteen chapters. The first chapter gives an introduction to Python and its relevance and scope in contemporary data analysis contexts. Ch. 2 teaches the basics and Python coding, Ch. 3-7, provide a step-by-step narration of how to enter data, process it, preliminary analysis and data cleaning with the help of Python, Ch.8-9, present data visualizations and narration techniques using Python; Ch.10.demonstrate how Python can use for statistical analysis. The remaining chapters are focusing on giving more real life situations in data analysis and the practical solutions to handle them. The exercises provided in the book are similar to real analysis situations, and that will help the reader for an easy transition to the data analyst jobs. The authors have taken utmost care identifying and providing solutions to all practical difficulties the readers may face while using Python for data analysis purpose. The authors have developed a series of codes and have incorporated them to make data processing and analysis convenient and easy for the researchers. The self-learning materials given in this book will help social science and marketing researchers to deepen their understanding of various steps in data processing and analyses and to gain advanced skills in using Python for this purpose.

ISE Essentials of Marketing Analytics

Author : Dana E. Harrison
Publisher :
ISBN 13 : 9781260597745
Total Pages : 512 pages
Book Rating : 4.5/5 (977 download)

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Book Synopsis ISE Essentials of Marketing Analytics by : Dana E. Harrison

Download or read book ISE Essentials of Marketing Analytics written by Dana E. Harrison and published by . This book was released on 2021-02-09 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Data Analytics for Marketing

Author : Guilherme Diaz-Bérrio
Publisher : Packt Publishing Ltd
ISBN 13 : 1801813833
Total Pages : 452 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Data Analytics for Marketing by : Guilherme Diaz-Bérrio

Download or read book Data Analytics for Marketing written by Guilherme Diaz-Bérrio and published by Packt Publishing Ltd. This book was released on 2024-05-10 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conduct data-driven marketing research and analysis with hands-on examples using Python by leveraging open-source tools and libraries Key Features Analyze marketing data using proper statistical techniques Use data modeling and analytics to understand customer preferences and enhance strategies without complex math Implement Python libraries like DoWhy, Pandas, and Prophet in a business setting with examples and use cases Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMost marketing professionals are familiar with various sources of customer data that promise insights for success. There are extensive sources of data, from customer surveys to digital marketing data. Moreover, there is an increasing variety of tools and techniques to shape data, from small to big data. However, having the right knowledge and understanding the context of how to use data and tools is crucial. In this book, you’ll learn how to give context to your data and turn it into useful information. You’ll understand how and where to use a tool or dataset for a specific question, exploring the "what and why questions" to provide real value to your stakeholders. Using Python, this book will delve into the basics of analytics and causal inference. Then, you’ll focus on visualization and presentation, followed by understanding guidelines on how to present and condense large amounts of information into KPIs. After learning how to plan ahead and forecast, you’ll delve into customer analytics and insights. Finally, you’ll measure the effectiveness of your marketing efforts and derive insights for data-driven decision-making. By the end of this book, you’ll understand the tools you need to use on specific datasets to provide context and shape your data, as well as to gain information to boost your marketing efforts.What you will learn Understand the basic ideas behind the main statistical models used in marketing analytics Apply the right models and tools to a specific analytical question Discover how to conduct causal inference, experimentation, and statistical modeling with Python Implement common open source Python libraries for specific use cases with immediately applicable code Analyze customer lifetime data and generate customer insights Go through the different stages of analytics, from descriptive to prescriptive Who this book is for This book is for data analysts and data scientists working in a marketing team supporting analytics and marketing research, who want to provide better insights that lead to data-driven decision-making. Prior knowledge of Python, data analysis, and statistics is required to get the most out of this book.

Marketing Analytics

Author : Mike Grigsby
Publisher : Kogan Page Publishers
ISBN 13 : 0749482176
Total Pages : 241 pages
Book Rating : 4.7/5 (494 download)

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Book Synopsis Marketing Analytics by : Mike Grigsby

Download or read book Marketing Analytics written by Mike Grigsby and published by Kogan Page Publishers. This book was released on 2018-04-03 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Who is most likely to buy and what is the best way to target them? How can businesses improve strategy without identifying the key influencing factors? The second edition of Marketing Analytics enables marketers and business analysts to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, this book offers a welcome handbook on how statistics, consumer analytics and modelling can be put to optimal use. The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.

Marketing Research With R And Python

Author : Howard Pong-yuen Lam
Publisher : World Scientific
ISBN 13 : 9811277567
Total Pages : 297 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Marketing Research With R And Python by : Howard Pong-yuen Lam

Download or read book Marketing Research With R And Python written by Howard Pong-yuen Lam and published by World Scientific. This book was released on 2023-09-28 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is meant for readers with little or no experience in programming in R and Python, who wish to quickly learn what is necessary, and be able to conduct marketing research by running tests easily in R or Python.A number of marketing research textbooks have been using SPSS or SAS for many years. Conversely, R and Python can be downloaded and installed in a personal computer for free. Instructors and students do not have to go to a computer room in a university to use SPSS or SAS anymore. Instead, students can run R or Python on their personal computers.For any company, growth comes either from organic growth of existing products, or from launching successful new products. Due to competition in the marketplace, each company's marketer must determine whether or not it is time to develop and launch a new product:This book covers important frameworks and concepts of marketing research for developing a new product.

Python Social Media Analytics

Author : Siddhartha Chatterjee
Publisher : Packt Publishing Ltd
ISBN 13 : 1787126757
Total Pages : 312 pages
Book Rating : 4.7/5 (871 download)

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Book Synopsis Python Social Media Analytics by : Siddhartha Chatterjee

Download or read book Python Social Media Analytics written by Siddhartha Chatterjee and published by Packt Publishing Ltd. This book was released on 2017-07-28 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

R For Marketing Research and Analytics

Author : Chris Chapman
Publisher : Springer
ISBN 13 : 3030143163
Total Pages : 487 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis R For Marketing Research and Analytics by : Chris Chapman

Download or read book R For Marketing Research and Analytics written by Chris Chapman and published by Springer. This book was released on 2019-03-28 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R for marketing research. This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications. The 2nd edition increases the book’s utility for students and instructors with the inclusion of exercises and classroom slides. At the same time, it retains all of the features that make it a vital resource for practitioners: non-mathematical exposition, examples modeled on real world marketing problems, intuitive guidance on research methods, and immediately applicable code.

Data Science for Marketing Analytics

Author : Mirza Rahim Baig
Publisher : Packt Publishing
ISBN 13 : 9781800560475
Total Pages : 636 pages
Book Rating : 4.5/5 (64 download)

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Book Synopsis Data Science for Marketing Analytics by : Mirza Rahim Baig

Download or read book Data Science for Marketing Analytics written by Mirza Rahim Baig and published by Packt Publishing. This book was released on 2021-09-07 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key Features: Use data analytics and machine learning in a sales and marketing context Gain insights from data to make better business decisions Build your experience and confidence with realistic hands-on practice Book Description: Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What You Will Learn: Load, clean, and explore sales and marketing data using pandas Form and test hypotheses using real data sets and analytics tools Visualize patterns in customer behavior using Matplotlib Use advanced machine learning models like random forest and SVM Use various unsupervised learning algorithms for customer segmentation Use supervised learning techniques for sales prediction Evaluate and compare different models to get the best outcomes Optimize models with hyperparameter tuning and SMOTE Who this book is for: This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

Quantitative Models in Marketing Research

Author : Philip Hans Franses
Publisher : Cambridge University Press
ISBN 13 : 1139428845
Total Pages : 222 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Quantitative Models in Marketing Research by : Philip Hans Franses

Download or read book Quantitative Models in Marketing Research written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2001-08-09 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in data collection and data storage techniques have enabled marketing researchers to study the individual characteristics of a large range of transactions and purchases, in particular the effects of household-specific characteristics. This 2001 book presents important and practically relevant quantitative models for marketing research. Each model is presented in detail with a self-contained discussion, which includes: a demonstration of the mechanics of the model, empirical analysis, real world examples, and interpretation of results and findings. The reader of the book will learn how to apply the techniques, as well as understand the methodological developments in the academic literature. Pathways are offered in the book for students and practitioners with differing numerical skill levels; a basic knowledge of elementary numerical techniques is assumed.

Text Analytics with Python

Author : Dipanjan Sarkar
Publisher : Apress
ISBN 13 : 1484223888
Total Pages : 397 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Text Analytics with Python by : Dipanjan Sarkar

Download or read book Text Analytics with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2016-11-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Practical Machine Learning for Data Analysis Using Python

Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128213809
Total Pages : 534 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Practical Machine Learning for Data Analysis Using Python by : Abdulhamit Subasi

Download or read book Practical Machine Learning for Data Analysis Using Python written by Abdulhamit Subasi and published by Academic Press. This book was released on 2020-06-05 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features