English | 2016 | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 1h 54m | 201 MB
Use your data to predict future events with the help of machine learning. This course will walk you through creating a machine learning prediction solution and will introduce Python, the scikit-learn library, and the Jupyter Notebook environment.
When working with data, machine learning can be used to do incredible things, including predicting future events. Its ease of use combined with the power of scikit-learn is causing Python to become the preferred development language for many machine learning practitioners. In this course, Understanding Machine Learning with Python, you will learn how Python developers and data scientists use machine learning to predict the likelihood of events based on data. Throughout this course, you will use Python and the scikit-learn library. Specifically, you will learn how to format your problem to be solvable, how to prepare your data for use in a prediction, and finally how to combine that data with algorithms to create models that can predict the future, all performed in the Jupyter Notebook environment. By the end of this course, you will have a better understanding of how machine learning can help you put your data to good use in predicting future events, and you’ll also know how to use Python to make it happen.