**Dell Technologies** and **NVIDIA** are excited to sponsor this Kaggle competition, inviting data scientists from around the world to showcase their skills and creativity. Participants are encouraged to leverage NVIDIA’s powerful toolkits and libraries, such as RAPIDS cuDF pandas, and RAPIDS suite, to significantly accelerate their data pre-processing and machine learning workflows.

These tools, combined with Dell’s high-performance Precision workstations powered by NVIDIA RTX™ Ada Generation GPUs, provide an optimal environment for tackling complex data science challenges.

You aren’t required to use these advanced technologies for your final solutions, however, please support our sponsors Dell Technologies and NVIDIA by familiarizing yourself with their technology listed below.

**Dell AI-ready Precision workstations**

Dell Precision workstations are high-performance computing solutions designed for professionals in fields such as computer-aided design, architecture, and data science. These workstations are available in both desktop and mobile forms, offering powerful processors, NVIDIA RTX Ada Generation GPUs, and substantial memory and storage capacities. They are engineered for reliability and optimized for demanding applications, making them ideal for data science tasks.

[Dell Precision 7960 Tower Workstation](https://www.dell.com/en-us/shop/desktop-computers/precision-7960-tower-workstation/spd/precision-t7960-workstation#features_section)

[Dell Precision 5860 Tower Workstation](https://www.dell.com/en-us/shop/desktop-computers/precision-5860-tower/spd/precision-5860-workstation#features_section)

[Dell Precision 7780 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-17-7780-laptop#features_section)

[Dell Precision 7680 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-16-7680-laptop#features_section)

[Dell Precision 5690 Mobile Workstation](https://www.dell.com/en-us/shop/cty/pdp/spd/precision-16-5690-laptop#features_section)

**NVIDIA RTX Ada Generation GPUs**

NVIDIA RTX Ada Generation GPUs, powered by the Ada Lovelace architecture, are designed to deliver exceptional performance for professional visualization, AI, graphics, and data science workloads. These GPUs feature advanced technologies such as third-generation RT Cores for enhanced ray tracing, fourth-generation Tensor Cores for accelerated AI computations, and CUDA cores for improved single-precision floating-point operations. With substantial memory capacity and efficient processing capabilities, RTX Ada GPUs can handle large datasets and complex models, making them ideal for data science tasks. Their ability to accelerate AI and data processing workflows significantly reduces computation time, enabling data scientists to achieve faster insights and more efficient analyses.

Learn More - [https://www.nvidia.com/en-us/technologies/ada-architecture/](https://www.nvidia.com/en-us/technologies/ada-architecture/)

**NVIDIA RAPIDS** - [https://www.nvidia.com/en-au/deep-learning-ai/software/rapids/](https://www.nvidia.com/en-au/deep-learning-ai/software/rapids/)

NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and AI libraries designed to enhance the performance of data science workflows. By leveraging the power of GPUs, RAPIDS accelerates data manipulation, machine learning, and graph analytics, significantly reducing the time required for data processing and model training. It integrates seamlessly with popular data science tools like Pandas, scikit-learn, and Apache Arrow, allowing data scientists to utilize familiar APIs while benefiting from substantial speedups. RAPIDS is particularly valuable for data science because it enables faster experimentation, leading to quicker insights and more efficient model development. This acceleration is crucial in handling large datasets and complex computations, making RAPIDS an essential tool for modern data science projects.

Get Started - [https://developer.nvidia.com/rapids](https://developer.nvidia.com/rapids)

**NVIDIA cuDF pandas** - [https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/](https://developer.nvidia.com/blog/rapids-cudf-accelerates-pandas-nearly-150x-with-zero-code-changes/)

NVIDIA cuDF pandas is a GPU DataFrame library that provides a pandas-like API for loading, joining, aggregating, filtering, and manipulating data. By leveraging the power of GPUs, cuDF accelerates data processing tasks, making it up to 110x significantly faster than traditional CPU-based methods. This acceleration is particularly beneficial for data scientists working with large datasets, as it reduces the time required for data manipulation and analysis. cuDF pandas integrates seamlessly with other RAPIDS libraries and popular data science tools, allowing users to maintain their existing workflows while benefiting from enhanced performance. Its ability to handle complex computations efficiently makes cuDF pandas an essential tool for modern data science projects.

Get Started - https://github.com/rapidsai/cudf