Skip to content
TrackPodcasts
artsSep 27, 202519:09pending

Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

About this episode

Focuses on machine learning for tabular data, covering its fundamental concepts and practical applications. The sources explore various machine learning and deep learning approaches, with a particular emphasis on gradient boosting techniques like XGBoost and LightGBM, highlighting their efficacy with structured data. Readers will learn about data preparation, feature engineering, and advanced processing methods, including handling missing values and categorical features. The text also discusses model optimization, evaluation, and deployment strategies, demonstrating how to build and implement machine learning pipelines, including discussions on cloud platforms and generative AI tools that aid in these processes.

You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary

Get the Book now from Amazon:
https://www.amazon.com/Machine-Learning-Tabular-Data-XGBoost/dp/1633438546?&linkCode=ll1&tag=cvthunderx-20&linkId=de0b879ca6bb24b542f7419b514415e7&language=en_US&ref_=as_li_ss_tl

Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy

Get every episode summarized

Each time CyberSecurity Summary publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.

Email me new episodes

Free for 3 shows. No card needed.

Hosts & guests

No transcript yet

This episode has not been transcribed. Request it and it moves to the front of the queue.

Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

CyberSecurity Summary

0:00
19:09

More episodes

More from CyberSecurity Summary

View all episodes →