XGBoost Deep Dive w/ Python & Pandas | Hands-on Data Science

 

XGBoost Deep Dive w/ Python & Pandas | Hands-on Data Science

The course focuses on using the Python version of XGBoost, the best and most popular algorithm for tabular data, and teaches students how to use it effectively ...

Udemy Coupon Codes -- >  XGBoost Deep Dive w/ Python & Pandas | Hands-on Data Science

XGBoost is a popular open-source library for gradient boosting that is widely used in the field of machine learning. It is known for its high performance and ability to handle large datasets, making it a popular choice for tasks such as classification and regression.

A course on "XGBoost Deep Dive w/ Python & Pandas | Hands-on Data Science" would likely teach students how to use XGBoost in combination with Python and the Pandas library to build and evaluate machine learning models. This could include topics such as installing and configuring XGBoost, preparing data for model training, training and evaluating XGBoost models, and using XGBoost to make predictions on new data.

The course may also cover more advanced topics such as tuning XGBoost models for optimal performance, using XGBoost for tasks such as feature selection and feature importance, and using XGBoost in a production environment.

Overall, a course on "XGBoost Deep Dive w/ Python & Pandas | Hands-on Data Science" would be an excellent opportunity for anyone interested in using XGBoost to build and evaluate machine learning models. It would provide a comprehensive understanding of the tools and techniques needed to use XGBoost effectively, and would equip students with the knowledge and skills needed to succeed in this field.

What you'll learn

• Learn the top skill to become a Machine Learning Engineer or Data Scientist
• Learn XGBoost, the best and most popular algorithm for tabular data
• Leverage Pandas for Feature Engineering and data Visualization
• Understand how to define a machine learning project, going from raw data to a trained model
• Learn Gradient Boosting Decision Trees working with realistic datasets and Hands on projects
• Learn to apply XGBoost to NLP problems using Deep Learning and TF-IDF features
• Project 1: Supervised Regression problem where we predict AirBnB listings prices
• Project 2: Binary Classification problem where we work with actual logs of a website visits to predict online conversions
• Project 3: Multi Class text Classification. We work with large datasets and more than 200 classes
• Project 4: Time series Forecasting with XGBoost