21 ratings
Understand the theory and intuition behind machine learning classifiers such as Logistic Regression, Support Vector Machines, and Random Forest.
Compare trained models by calculating AUC score and plot ROC curve
Train various classifier models using Scikit-Learn library
In this hands-on project, we will train several classification algorithms such as Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Random Forest Classifier to predict the churn rate of Telecommunication Customers. Machine learning help companies analyze customer churn rate based on several factors such as services subscribed by customers, tenure rate, and payment method. Predicting churn rate is crucial for these companies because the cost of retaining an existing customer is far less than acquiring a new one. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Artificial Intelligence (AI)
Machine Learning
Python Programming
classification
Computer Programming
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Understand the problem statement and business case
Import libraries/datasets and perform Exploratory Data Analysis
Perform Data Visualization
Prepare the data before model training
Train and Evaluate a Logistic Regression model
Train and Evaluate a Support Vector Machine Model
Train and Evaluate a Random Forest Classifier model
Train and Evaluate a K-Nearest Neighbor model
Train and Evaluate a Naive Bayes Classifier model
Compare the trained models by calculating AUC score and plot ROC curve
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
Guided Projects are not eligible for refunds. See our full refund policy.
Financial aid is not available for Guided Projects.
Auditing is not available for Guided Projects.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
More questions? Visit the Learner Help Center.
