Auto Machine Learning (Auto ML) Bootcamp: Build 15 Projects - AI Summary

Applying traditional machine learning methods to real-world business problems is time-consuming, resource-intensive, and challenging. It requires experts in several disciplines, including data scientists – some of the most sought-after professionals in the job market right now. Manually constructing a machine learning model is a multistep process that requires domain knowledge, mathematical expertise, and computer science skills – which is a lot to ask of one company, let alone one data scientist (provided you can hire and retain one). Automated machine learning enables organizations to use the baked-in knowledge of data scientists without expending time and money to develop the capabilities themselves, simultaneously improving return on investment in data science initiatives and reducing the amount of time it takes to capture value. We'll cover everything you need to know for the full data science and machine learning tech stack required at the world's top companies.