LeonOnyx/Onyx_PowerBI_ML
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Machine learning is an important component of the growing field of data science. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. These insights subsequently drive decision making within applications and businesses, ideally impacting key growth metrics. As big data continues to expand and grow, the market demand for data scientists will increase, requiring them to assist in the identification of the most relevant business questions and subsequently the data to answer them. In this session we will learn how to use Automated Machine Learning to create and apply a binary prediction model in Power BI using Python, Anaconda and Pycaret to quickly classify data.
This project helps data analysts and business intelligence professionals quickly build and integrate machine learning predictions directly into their Power BI reports. You'll use your existing business data to train a model that can classify new information, and then see those predictions immediately within your dashboards to inform business decisions. This is ideal for a data professional who needs to add predictive insights to their reports without deep programming expertise.
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Use this if you want to add binary classification predictions (like 'yes/no' or 'churn/not churn') to your Power BI reports using an automated machine learning approach.
Not ideal if you need to build complex, custom machine learning models from scratch or require advanced model tuning outside of an automated framework.
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Python
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Last pushed
Oct 07, 2022
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