Learn how to make the right decisions for your business with the power of Python machine learning
Key Features
- Use the power of Python machine learning to make the right business decisions
- Follow real-life use cases from the business world to contextualize your learning
- Work your way through practical recipes that will reinforce what you have learned
Book Description
One of the most valuable uses of data science is in helping businesses make the right decisions. This is a complicated confluence of two disparate worlds, as well as a fiercely competitive market, so you’ll need all the guidance you can get.
Whether you’re a data scientist wanting to get a business-driven perspective, or you want the decisions in your business to be guided by the power of machine learning, The Art of Data-Driven Business Decisions will be your invaluable guide.
We start by looking at how to use Python and its many libraries for machine learning. Experienced data scientists may want to skip this short introduction, but we soon get into the meat of the book and look at the many and varied ways machine learning with Python can be applied to the domain of business decisions through real-world business problems that you can tackle yourself. You will gain priceless practical insights into the value that machine learning can provide to your business, as well as the technical ability to apply a wide variety of tried and tested machine learning methods.
By the end of this book, you will have learned the value of basing business decisions on data-driven methodologies, and you will have the Python skills to apply what you’ve learned in the real world.
What you will learn
- Scrape web pages for their data with Python
- Create effective dashboard with Seaborn
- Predict whether a customer will cancel a subscription to a service
- Analyze key pricing metrics with pandas
- Recommend the right products to your customers
- Determine the costs and benefits of promotions
- Segment your customers using clustering algorithms
- Use NLP and Scikit-Learn to improve digital advertisements
Who This Book Is For
The primary audience are data scientists, machine learning engineers and developers, data engineers, and business decision makers. They want to learn the skills to implement data science projects in the areas of marketing, sales, pricing, customer success, adtech, and more from a business perspective. They want to apply data science for business processes optimization. This book intends to provide a common ground of discussion for several audience profiles within a company. Book is for business people seeking to improve their knowledge on how can data science can be used to improve business operations, and for individuals with technical skills who want to implement successful data science projects within a company and want to back their technical proposal with a strong business case.
Table of Contents
- Data Analysis and Visualization with Pandas and Seaborn
- Machine Learning with Sci-Kit Learn
- Market Trend Insights
- Customer and Product Segmentation
- Estimating Customer Satisfaction
- Predicting Churn and Conversion
- Performing Pricing Analytics
- Forecasting Sales and Recommending Products
- Optimizing Promotion and Stock
- Improving Digital Marketing Strategy
- Interviewing Business Leaders
Alan Bernardo Palacio is a data scientist and an engineer with vast experience in different engineering fields. His focus has been the development and application of state-of-the-art data products and algorithms in several industries. He has worked for companies such as Ernst and Young, Globant, and now holds a data engineer position at Ebiquity Media helping the company to create a scalable data pipeline. Alan graduated with a Mechanical Engineering degree from the National University of Tucuman in 2015, participated as the founder in startups, and later on earned a Master's degree from the faculty of Mathematics in the Autonomous University of Barcelona in 2017. Originally from Argentina, he now works and resides in the Netherlands.
