XGBoost
![Decorative image of NVFLARE use cases.](https://developer-blogs.nvidia.com/wp-content/uploads/2024/06/nvflare-2-4-featured-960x540.jpeg)
Jun 28, 2024
Federated XGBoost Made Practical and Productive with NVIDIA FLARE
XGBoost is a highly effective and scalable machine learning algorithm widely employed for regression, classification, and ranking tasks. Building on the...
6 MIN READ
![A diagram representing multi-GPU training.](https://developer-blogs.nvidia.com/wp-content/uploads/2023/08/multi-gpu-training-960x540.png)
Sep 07, 2023
Unlocking Multi-GPU Model Training with Dask XGBoost
As data scientists, we often face the challenging task of training large models on huge datasets. One commonly used tool, XGBoost, is a robust and efficient...
11 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2023/06/federated-ml-nvidia-flare-featured-1-960x540.jpg)
Jun 22, 2023
Applying Federated Learning to Traditional Machine Learning Methods
In the era of big data and distributed computing, traditional approaches to machine learning (ML) face a significant challenge: how to train models...
3 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2023/02/xgboost-categorical-featured.png)
Feb 08, 2023
Categorical Features in XGBoost Without Manual Encoding
XGBoost is a decision-tree–based, ensemble machine learning algorithm based on gradient boosting. However, until recently, it didn’t natively support...
5 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2022/10/dli-workshops-anomaly-detection-social-1780716-set1-li-tw-2048x1024-v3.jpg)
Oct 13, 2022
Upcoming Workshop: Applications of AI for Anomaly Detection
Learn to detect data abnormalities before they impact your business by using XGBoost, autoencoders, and GANs. Workshops are available in both the NALA and EMEA...
1 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2022/09/gpu-accelerated-shap-tech-blog-featured-image-5-2.png)
Oct 05, 2022
Explain Your Machine Learning Model Predictions with GPU-Accelerated SHAP
Machine learning (ML) is increasingly used across industries. Fraud detection, demand sensing, and credit underwriting are a few examples of specific use...
15 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2022/02/Real-time_featured-Image.jpg)
Feb 02, 2022
Real-time Serving for XGBoost, Scikit-Learn RandomForest, LightGBM, and More
The success of deep neural networks in multiple areas has prompted a great deal of thought and effort on how to deploy these models for use in real-world...
7 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2021/09/shap-extendedai.png)
Jan 13, 2022
Accelerating Trustworthy AI for Credit Risk Management
On April 21, 2021, the EU Commission of the European Union issued a proposal for a regulation to harmonize the rules governing the design and marketing of AI...
13 MIN READ
![Graphic with black background with DLI anomaly course name](https://developer-blogs.nvidia.com/wp-content/uploads/2021/08/DLI-Anomoly-detection.png)
Dec 15, 2021
NVIDIA DLI Teaches Supervised and Unsupervised Anomaly Detection
The NVIDIA Deep Learning Institute (DLI) is offering instructor-led, hands-on training on how to build applications of AI for anomaly detection. Anomaly...
5 MIN READ
![Graphic with black background with DLI anomaly course name](https://developer-blogs.nvidia.com/wp-content/uploads/2021/08/DLI-Anomoly-detection.png)
Aug 02, 2021
Learn How to Build Applications of AI for Anomaly Detection
Whether you need to monitor cybersecurity threats, fraudulent financial transactions, product defects, or equipment health, artificial intelligence can help you...
2 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2021/06/Accelerate-XGBoost_Featured-Image.jpg)
Jun 17, 2021
Accelerating XGBoost on GPU Clusters with Dask
In XGBoost 1.0, we introduced a new official Dask interface to support efficient distributed training. Fast-forwarding to XGBoost 1.4, the interface is...
11 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2021/06/Advancing-the-State_Pic3.png)
Jun 09, 2021
Advancing the State of the Art in AutoML, Now 10x Faster with NVIDIA GPUs and RAPIDS
To achieve state-of-the-art machine learning (ML) solutions, data scientists often build complex ML models. However, these techniques are computationally...
16 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2021/03/NASA-and-NVIDIA2_Pic1.png)
Apr 19, 2021
NASA and NVIDIA Collaborate to Accelerate Scientific Data Science Use Cases, Part 2
Over the past couple of years, NVIDIA and NASA have been working closely on accelerating data science workflows using RAPIDS, and integrating these...
6 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2021/03/NASA-and-NVIDIA_Pic.png)
Apr 08, 2021
NASA and NVIDIA Collaborate to Accelerate Scientific Data Science Use Cases, Part 1
Over the past couple of years, NVIDIA and NASA have been working closely on accelerating data science workflows using RAPIDS and integrating these...
7 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2020/10/SHAP-value.png)
Nov 12, 2020
Explaining and Accelerating Machine Learning for Loan Delinquencies
Machine learning (ML) can extract deep, complex insights out of data to help make decisions. In many cases, using more advanced models delivers real...
16 MIN READ
![](https://developer-blogs.nvidia.com/wp-content/uploads/2020/02/rank-time_thumbnail.jpg)
Feb 14, 2020
Learning to Rank with XGBoost and GPU
XGBoost is a widely used machine learning library, which uses gradient boosting techniques to incrementally build a better model during the training phase by...
13 MIN READ