Machine Learning Journey

What does Siri, Alexa and Google Play have in common?How is Capital One and Paypal able to instantly detect fraudulent transfers?How is Google Photos able to identify faces in photos? How is Youtube able to make wickedly smart suggested videos?Or Amazon know what you want before you do?How does FexEx know the best routes and time of day to ship packages?These are all made possible through Machine Learning algorithms and in this course, you will not only understand them but you will actually BUILD machine learning models in Python.  And you will use them to make predictions on data!  Not only that, you will learn how to validate your models are accurate so you can prove to your peers and superiors that your models are trustworthy.Have always been a little interested in Machine Learning but have been a little intimidated by the math?Do you feel like you're way behind the times and it's too late to get in on the ML Hype?Maybe you feel like coding in Python and Data Science sounds too hard.  Is that you?If you answered yes to any of those questions this course is for you.  I built this course for complete beginners and had a blast building it for you guys.Here's a few of things you will build in this course:How to setup the perfect development environment for coding ML AlgorithmsHow to use Anaconda, VSCode, Jupyter Notebooks and Python3 to build and test accurate ML modelsHow to build the perfect preprocessing template for ML engineeringHow to understand what One Hot encoding is and why it's importantHow to use the Numpy, Pandas, Matplotlib and Seaborn Python libraries to build beautiful ML modelsUnderstanding Feature Scaling and when you would use it7 steps to understanding and building Simple Linear Regression models7 steps to understanding and building M