New York, United States
The Non-degree in Mining Quality Prediction Using Machine & Deep Learning at Coursera Project Network is a program for international students taught in English.
The Coursera Project Network is a unique initiative within Coursera, a leading online learning platform founded in 2012. It is not a university, but rather a public, open-access platform that facilitates the creation and delivery of hands-on projects by experts and educators. The Coursera Project Network is distinguished by its focus on practical, project-based learning, enabling learners to apply their skills in real-world scenarios. This approach allows individuals to gain tangible, job-ready skills quickly and efficiently.
In this 1.5-hour long project-based course, you will be able to:- Understand the theory and intuition behind Simple and Multiple Linear Regression.- Import Key python libraries, datasets and perform data visualization- Perform exploratory data analysis and standardize the training and testing data.- Train and Evaluate different regression models using Sci-kit Learn library.- Build and train an Artificial Neural Network to perform regression.- Understand the difference between various regression models KPIs such as MSE, RMSE, MAE, R2, and adjusted R2.- Assess the performance of regression models and visualize the performance of the best model using various KPIs.
The Coursera Project Network offers a wide range of guided projects across various domains, including business, technology, data science, and more. These projects are designed to be completed in a short time frame, typically a few hours, providing learners with a quick and immersive learning experience. Through step-by-step instructions and hands-on practice, participants can build confidence in their abilities and directly apply what they learn to their personal or professional pursuits. The Coursera Project Network empowers learners to bridge the gap between theoretical knowledge and practical application, making it a valuable resource for skill development and career advancement.
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