Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.  Abstract This week on Making Data Simple, our guest is Frank Kane, Founder of Sundog Software. Frank's diverse career has allowed him to develop a thorough understanding of various data science and business concepts. The conversation ranges from how Frank got his start developing video games, to the importance of maintaining your skills for personal marketability. Host Al Martin and Frank also discuss the growing concern for ethics in computing that may be unknown to some.    Connect with Frank LinkedIn Sundog Education Udemy Twitter Show Notes 07:07 - See here how Netflix uses machine learning to recommend what to watch.  13:21 - "Good intention are not enough." Click here to checkout a similar Forbes article. 15:52 - Check out this medium article, emphasizing the need for humanities majors in tech. 27:18 - Here are 5 ways to keep up your coding skills while working as a manager. Connect with the Team Producer Liam Seston - LinkedIn. Producer Lana Cosic - LinkedIn. Producer Meighann Helene - LinkedIn.  Producer Mark Simmonds - LinkedIn.  Host Al Martin - LinkedIn and Twitter. Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

This book introduces you to the world of Big Data processing using Apache Spark and Python. You will learn to set up and run Spark on different systems, process massive datasets, and create solutions to real-world Big Data challenges with over 15 hands-on examples included. What this Book will help me do Understand the basics of Apache Spark and its ecosystem. Learn how to process large datasets with Spark RDDs using Python. Implement machine learning models with Spark's MLlib library. Master real-time data processing with Spark Streaming modules. Deploy and run Spark jobs on cloud clusters using AWS EMR. Author(s) Frank Kane spent 9 years working at Amazon and IMDb, handling and solving real-world machine learning and Big Data problems. Today, as an instructional designer and educator, he brings his wealth of experience to learners around the globe by creating accessible, practical learning resources. His teaching is clear, engaging, and designed to prepare students for real-world applications. Who is it for? This book is ideal for data scientists or data analysts seeking to delve into Big Data processing with Apache Spark. Readers who have foundational knowledge of Python, as well as some understanding of data processing principles, will find this book useful to sharpen their skills further. It is designed for those eager to learn the practical applications of Big Data tools in today's industry environments. By the end of this book, you should feel confident tackling Big Data challenges using Spark and Python.