DataCamp

Feature Engineering for Machine Learning in Python

Engineering and Technology

Short Description

Create new features to improve the performance of your Machine Learning models.

Long Description

In today's rapidly evolving world, machine learning applications are constantly making groundbreaking advancements. However, it is often overlooked that a significant amount of data manipulation and feature engineering is required before these sophisticated models can be effectively utilized. This course aims to equip you with the necessary skills to perform these crucial tasks. Throughout the course, you will delve into the Stack Overflow Developers survey and historic US presidential inauguration addresses. By doing so, you will gain a comprehensive understanding of the most effective methods for preprocessing and engineering features from various types of data, including categorical, continuous, and unstructured data. By participating in this course, you will gain valuable hands-on experience in preparing data for your own machine learning models. This practical knowledge will empower you to confidently tackle any dataset and optimize it for successful machine learning applications.

Course Details

Duration
4 hours
Format
Short Course
Price
USD39.00
Course Link
More Information
DataCamp
Description
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.