HP TECH TAKES /...
Exploring today's technology for tomorrow's possibilities
Subscribe
4 Best HP Laptops for Data Science and Data Analysis
Tom Gerencer
|
November 16, 2022
The purpose of a given data science endeavor is to extract or produce value from data by developing models that employ algorithms and statistical methods. The magnitude of the value produced is a function of the quality of the model ultimately put into production. That quality is measured in speed, accuracy, recall, and precision. How well that model performs is due in large part to the quality of the data, algorithms, training, and testing.
Today’s data science workflows are accomplished by individuals and teams alike in hybrid work environments, with computing spanning local hardware, clusters, and cloud instances. Data engineers, data scientists, ML ops engineers, and data analysts can all be shackled in their effectiveness if their hardware becomes a bottleneck for their workflows.
The size and complexity of both data and models are exploding exponentially, and so is the computing power needed to train and deploy cutting-edge machine learning, deep learning, and AI models.
RAM
More memory means faster processing. The lifeblood of your computer's speed and performance is the amount of Random Access Memory (RAM) available. Look for more memory if you're working with larger datasets. With 175 zettabytes of data worldwide projected by 2025, and the average deep learning model training on 1 petabyte of data before deployment, future-proofing your laptop means ensuring memory does not become a bottleneck.
For data science applications and workflows, 16GB of RAM is recommended. If you’re looking to train large complex models locally, HP offers configurations of up to 128GB of blazing-fast DDR5 RAM.
Processor
Data scientists need more and more processing power, hardware compatibility, power efficiency, and thermal management in the processors. The computer doesn’t work without the CPU and for those data engineers or analysts whose work is more CPU intensive, Z by HP mobile workstations offer the highest performance Intel® Core™ i9 CPUs with ECC memory.
SSD storage
Computing power is only half of the model training equation, so of course, you need to get the data to where your compute power is. For those who can store training data locally, Z mobile workstations offer up to 12TB of storage. Once that threshold is exceeded, data storage may need to migrate to either local servers or cloud storage instances.
Graphics cards
Why do graphics matter for the best data science laptops? Parallelization. GPU architecture lends itself well to machine learning and deep learning training and inferencing workflows. Model training on the GPU can be many many times faster than on a CPU. A standard CPU has 4 to 8 processing cores, but the average GPU has 700 cores, and some have 2,000 or more. NVIDIA® created the CUDA parallel computing platform to leverage that parallel computing power for data science. To run CUDA, you’ll want an HP laptop with a CUDA-capable GPU. Additionally, the Z by HP Data Science Stack Manager requires an NVIDIA GPU to run.
HP Software for Data Science
In order to get up and running on data science work as quickly as possible, HP offers the Data Science Stack Manager for both Ubuntu and WSL (Windows Subsystem for Linux 2). This software application provides one-click installment of a curated and managed Data Science Software Stack. It is available pre-loaded from the factory and to download from www.zdocs.datacience.hp.com.
The best HP mobile workstations for data science
Ready to dive in? Here’s our list of HP’s 4 best laptops for data science. Each one is fully customizable, so don’t be afraid to pick one as a starting point and dial up the RAM, storage, and processor as needed.
1. HP ZBook Fury G9
The ZBook Fury G9 is so powerful that you will forget that it’s a laptop. The combination of a desktop-class CPU, a massive amount of memory, and ultra high-end GPU makes the Fury capable of handling any data science workflow. From data engineers ingesting, cleaning, and preparing giant batch or streaming data sets to data scientists training an ML model, the ZBook Fury G9 can do it all.
Well suited for:
- Model training (structured and unstructured datasets) and inferencing
- Data processing and preparation
- Data scientists and data engineers
Specs
- Windows 11, WSL 2, Certified Linux® Ubuntu 20.04
- Up to Intel Core i9 processor
- Up to 128GB SODIMM DDR5 RAM
- Up to NVIDIA RTX™ A5500 Laptop GPU
- Up to 12TB PCIe NVME SSD
2. HP ZBook Studio G9
The ZBook Studio G9 is powerfully immersive and perfectly sized. It is packed with professional performance in an incredibly sleek PC enabling you to prepare and analyze data or build and train AI models, from anywhere.
Well suited for:
- Model training with structured data and inferencing
- Data processing and preparation
- Low-latency data analytics
- Graphically intensive data visualization
- Data scientists, data engineers, data analysts, and ML Ops engineers
Specs
- Windows 11, WSL 2, Certified Linux Ubuntu 20.04
- Up to Intel Core i9 processor
- Up to 64GB SODIMM DDR5 RAM
- Up to NVIDIA RTX A5500 Laptop GPU
- Up to 4TB PCIe® Gen4 x4 NVMe
3. HP ZBook Power G9
For the data professional who wants to power through both data science and productivity workflows, the ZBook Power G9 provides an outstanding mix of computing power and portability. This laptop allows you to connect, communicate, and collaborate on the go or dive deep into an Ubuntu-based machine learning model inside of the Windows Subsystem for Linux 2.
Well suited for:
- Data analytics
- Data visualization
- Data engineers and data analysts
Specs
- Windows 11 with WSL 2
- Up to 12th Gen Intel Core i9 processor
- Up to 32GB of SDRAM
- Up to NVIDIA RTX A2000 Laptop GPU
- Up to 8TB of PCIe NVME storage
4. HP ZBook Firefly G9
The ZBook Firefly G9 steps up pro-level performance with no increase in size. It combines performance with true mobility, providing everything you need to collaborate and manage projects from anywhere. When combined with a remote desktop solution like HP Anyware, the ZBook Firefly becomes a high-performance portal into a massive computing machine like the HP Z8 desktop, a cluster of workstations, a data center, or a cloud instance.
Well suited for:
- Remote connections to more powerful computing sources
- Data science teams
Specs
- Windows 11 with WSL 2
- Up to 12th Gen Intel Core i7 processor
- Up to 64GB of RAM
- Up to NVIDIA RTX A500 laptop GPU
- Up to 2TB of PCIe NVME storage
In summary
Big data is growing exponentially, but with distributed solutions, should data scientists worry about RAM, storage, and other specs? Yes. More and more data is being produced, cleaned, processed, and deployed at the edge. Even for those who leverage cloud instances or Kubernetes clusters for computing, the best laptops for data science have more RAM, cores, and in some cases CUDA-capable GPUs for mega-boosted parallel computing while enabling total team productivity from anywhere.
[1] Full Stack ML; How Much Memory Does A Data Scientist Need?
[2] High Scalability; How Big Is A Petabyte, Exabyte, Zettabyte, Or A Yottabyte?
[3] NVIDIA; What is CUDA?
[4] Khronos Group; OpenCL Overview
Related articles:
About the Author: Tom Gerencer is a contributing writer for HP® Tech Takes. Tom is an ASJA journalist, career expert at Zety.com, and a regular contributor to Boys' Life and Scouting magazines. His work is featured in The Boston Globe, Costco Connection, FastCompany, and many more.
