Pay in installments of $57.53 with
,
and
Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Aug 18 - Aug 23
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
Lenovo SFP (mini-GBIC) ModuleUpgrade your data networking with the Lenovo SFP (mini GBIC) Module, a purpose built copper based transceiver designed to deliver dependable Gigabit Ethernet performance through a single, compact SFP form factor. This 1 pack module brings 1000Base T capability to your Lenovo infrastructure, enabling high speed uplinks and flexible connectivity for servers, switches, and storage appliances. Its engineered to seamlessly integrate with Lenovo networking
Upgrade your data networking with the Lenovo SFP (mini-GBIC) Module, a purpose-built copper-based transceiver designed to deliver dependable Gigabit Ethernet performance through a single, compact SFP form factor. This 1-pack module brings 1000Base-T capability to your Lenovo infrastructure, enabling high-speed uplinks and flexible connectivity for servers, switches, and storage appliances. It’s engineered to seamlessly integrate with Lenovo networking ecosystems, including blade servers and enterprise switches, offering a streamlined upgrade path that minimizes downtime and maximizes network efficiency. Whether you’re refreshing an aging copper network, expanding an iSCSI storage fabric, or provisioning new virtualized workloads, this Lenovo SFP module delivers reliable, straightforward performance that you can trust in mission-critical environments. It combines a compact mini-GBIC design with robust build quality, ensuring long-term reliability in data centers, edge sites, and corporate campuses where persistent 1 Gbps links are essential for smooth data flows and storage access.
- Gigabit performance over copper with 1000Base-T compatibility delivers up to 1000 Mbps for storage networking, virtualization, and bandwidth-intensive applications, enabling efficient iSCSI traffic and fast data access.
- Compact SFP (mini-GBIC) form factor fits a wide range of Lenovo servers and switches, enabling dense uplinks, streamlined cabling, and flexible rack design for modern data centers.
- RJ-45 1000Base-T copper port supports standard twisted-pair cabling (Cat5e/Cat6) with distances up to 100 meters per link, simplifying deployments across campuses, labs, and enterprise networks.
- Hot-swappable, plug-and-play design minimizes downtime; insert into the appropriate SFP slot and connect your network cable to achieve immediate link activity without complex reconfigurations.
- One-pack packaging provides a ready-to-use, single-transceiver solution for IT teams managing multiple devices, with Lenovo engineering quality and dependable warranty support for enterprise reliability.
Technical Details of Lenovo SFP (mini-GBIC) Module
- Interface: 1 x RJ-45 1000Base-T copper port
- Data rate: Up to 1 Gbps Ethernet (1,000 Mbps)
- Cable type: Twisted-pair copper cabling (Cat5e/Cat6 compatible)
- Distance: Up to 100 meters (328 feet) per link
- Form factor: SFP (mini-GBIC); hot-swappable
- Industry standard: 1000Base-T; compliant with SFP specifications
- Compatibility: Designed for Lenovo networking gear and other SFP-enabled devices
- Package: 1-pack SFP module
- Environment: Suitable for data centers, enterprise networks, and storage networks requiring reliable copper uplinks
How to install Lenovo SFP (mini-GBIC) Module
- Power down the equipment or follow your data center’s hot-swappable guidelines if supported, to minimize risk and protect connected hardware.
- Identify the correct SFP slot on your Lenovo server, switch, or storage device and verify compatibility with 1000Base-T copper modules.
- Remove the existing module (if present) by gently pressing the release latch and pulling the module straight out from the slot.
- Align the Lenovo SFP module with the slot and insert it firmly until it clicks into place and the latch locks automatically.
- Connect a standard RJ-45 copper Ethernet cable to the module, ensuring a snug connection and verifying link activity on both the host device and the switch.
- Power on the device (if required) and configure the network interface as a 1000Base-T port, confirm speed negotiation, and adjust any storage network settings (MTU, iSCSI targets) as needed for optimal performance.
Frequently asked questions
- What is the Lenovo SFP (mini-GBIC) Module used for? It provides a copper-based 1 Gbps Ethernet uplink via an RJ-45 1000Base-T port, ideal for connecting Lenovo servers and switches to storage networks, virtualization hosts, and core network fabrics.
- Is this module compatible with non-Lenovo hardware? Yes, 1000Base-T SFP modules are broadly compatible with other vendor switches and NICs that support copper-based 1000 Mbps SFP, but always confirm compatibility with your specific device model and firmware version.
- What cabling should I use? Use standard twisted-pair copper cables, such as Cat5e or Cat6, with RJ-45 connectors to achieve reliable links up to the 100-meter specification per segment.
- Can I use this module for iSCSI traffic? Yes, a 1 Gbps copper SFP module is well-suited for iSCSI storage networks, providing cost-effective uplinks in small to medium deployments and complementing faster Ethernet fabrics elsewhere in the network.
- How can I verify the module is functioning? Check the link and activity LEDs on the SFP slot and on connected devices; monitor port status in your switch or server management interface for speed (1 Gbps), duplex mode, and error counters.
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- Standard Shipping : 3-10 business days
- If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
- Please click here for more details>>> Return & Exchange Policy
4.6 ★★★★★
Based on 7 reviews
Sort
Product Reviews
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents.
The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!!
The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!!
I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge.
Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents.
Personally I was disappointed by lack of any example on time series.
Must have for ML practitioner as a reference and guide.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book.
For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch.
For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min).
From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures.
I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications.
Several textbook editions later, what is different about this new edition?
First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills.
Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like.
Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026