Machine Learning in Power BI (English Explanation)

🌟 Course Description:

Welcome to "Machine Learning in Power BI" – your ultimate guide to blending the analytical prowess of Power BI with the predictive power of Azure Machine Learning! 🤖📊

About the Course: The goal of this course is to seamlessly integrate Power BI with Azure Machine Learning to provide you with a robust machine learning model. By the end of this course, you will be able to:

1. Introduction to Machine Learning 🎩

   • Discover the fundamentals of machine learning and its applications.

2. Machine Learning Types 🧠

   • Explore the different types of machine learning: Supervised, Unsupervised & Reinforcement Learning, understand their definitions, and tackle the challenges associated with each.

3. Automatic Machine Learning Process in Power BI 🚀

   • Learn how to automate the machine learning process within Power BI, making it easy for you to integrate predictive analytics into your dashboards.

4. Requirements to Start Machine Learning in Power BI 📋

   • Identify what you need before diving into machine learning with Power BI.

5. Step by Step Machine Learning Model Implementation 🕵️‍♂️

   • Follow a detailed, step-by-step guide to implement a machine learning model in Power BI.

6. Recall vs Precision: Machine Learning Performance Terms 🔍

   • Understand the key performance metrics used after training your machine learning model.

7. Confusion Matrix 📊

   • Dive into a confusion matrix to manage and interpret true positives, true negatives, false positives, and false negatives effectively.

8. Cost-Benefit Analysis 💰

   • Evaluate the cost versus benefits of implementing machine learning models in your business context.

9. AUC (Area Under Curve) vs ROC (Received Operating Characteristic) 📈

   • Learn about the significance of AUC and ROC as standard metrics for evaluating the performance of a model.

10. Training Details Report & Different Learning Algorithms 🛠️

    • Get hands-on with training reports and explore various learning algorithms to determine which is best suited for your data.

11. Apply Machine Learning Model 📈

    • Apply the machine learning model you've trained to new datasets and predict outcomes.

12. Analyze Machine Learning Model in Power BI Desktop 🧐

    • Analyze your machine learning model within Power BI Desktop, gaining insights that can drive business decisions.

By the end of this course, you will have a solid understanding of how to incorporate machine learning into your Power BI dashboards, enabling you to make data-driven decisions with confidence. Join us on this journey to transform your data into actionable insights! 🚀💫