Data Science for Marketing Analytics 상세페이지
Data Science for Marketing Analytics
Achieve your marketing goals with the data analytics power of Python
- 관심 0
소장
전자책 정가
22,000원
판매가
22,000원
출간 정보
- 2019.02.28 전자책 출간
듣기 기능
TTS(듣기) 미지원
파일 정보
- 420 쪽
- 6.8MB
지원 환경
- 앱
- 웹
- PC뷰어
- PAPER
ISBN
9781789952100
ECN
-
Data Science for Marketing Analytics
작품 정보
▶What You Will Learn
⦁ Analyze and visualize data in Python using pandas and Matplotlib
⦁ Study clustering techniques, such as hierarchical and k-means clustering
⦁ Create customer segments based on manipulated data
⦁ Predict customer lifetime value using linear regression
⦁ Use classification algorithms to understand customer choice
⦁ Optimize classification algorithms to extract maximal information
▶Key Features
⦁ Study new techniques for marketing analytics
⦁ Explore uses of machine learning to power your marketing analyses
⦁ Work through each stage of data analytics with the help of multiple examples and exercises
▶Who 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.
▶Audience
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.
▶Approach
Data Science for Marketing Analytics takes a hands-on approach to the practical aspects of using Python data analytics libraries to ease marketing analytics efforts. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.
⦁ Analyze and visualize data in Python using pandas and Matplotlib
⦁ Study clustering techniques, such as hierarchical and k-means clustering
⦁ Create customer segments based on manipulated data
⦁ Predict customer lifetime value using linear regression
⦁ Use classification algorithms to understand customer choice
⦁ Optimize classification algorithms to extract maximal information
▶Key Features
⦁ Study new techniques for marketing analytics
⦁ Explore uses of machine learning to power your marketing analyses
⦁ Work through each stage of data analytics with the help of multiple examples and exercises
▶Who 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.
▶Audience
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.
▶Approach
Data Science for Marketing Analytics takes a hands-on approach to the practical aspects of using Python data analytics libraries to ease marketing analytics efforts. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.
작가 소개
⦁ Tommy Blanchard
Tommy Blanchard earned his PhD from the University of Rochester and did his postdoctoral training at Harvard. Now, he leads the data science team at Fresenius Medical Care North America. His team performs advanced analytics and creates predictive models to solve a wide variety of problems across the company.
⦁ Debasish Behera
Debasish Behera works as a data scientist for a large Japanese corporate bank, where he applies machine learning/AI to solve complex problems. He has worked on multiple use cases involving AML, predictive analytics, customer segmentation, chat bots, and natural language processing. He currently lives in Singapore and holds a Master's in Business Analytics (MITB) from the Singapore Management University.
⦁ Pranshu Bhatnagar
Pranshu Bhatnagar works as a data scientist in the telematics, insurance, and mobile software space. He has previously worked as a quantitative analyst in the FinTech industry and often writes about algorithms, time series analysis in Python, and similar topics. He graduated with honors from the Chennai Mathematical Institute with a degree in Mathematics and Computer Science and has completed certification courses in Machine Learning and Artificial Intelligence from the International Institute of Information Technology, Hyderabad. He is based in Bangalore, India.
Tommy Blanchard earned his PhD from the University of Rochester and did his postdoctoral training at Harvard. Now, he leads the data science team at Fresenius Medical Care North America. His team performs advanced analytics and creates predictive models to solve a wide variety of problems across the company.
⦁ Debasish Behera
Debasish Behera works as a data scientist for a large Japanese corporate bank, where he applies machine learning/AI to solve complex problems. He has worked on multiple use cases involving AML, predictive analytics, customer segmentation, chat bots, and natural language processing. He currently lives in Singapore and holds a Master's in Business Analytics (MITB) from the Singapore Management University.
⦁ Pranshu Bhatnagar
Pranshu Bhatnagar works as a data scientist in the telematics, insurance, and mobile software space. He has previously worked as a quantitative analyst in the FinTech industry and often writes about algorithms, time series analysis in Python, and similar topics. He graduated with honors from the Chennai Mathematical Institute with a degree in Mathematics and Computer Science and has completed certification courses in Machine Learning and Artificial Intelligence from the International Institute of Information Technology, Hyderabad. He is based in Bangalore, India.
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