Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Jul 6 - Jul 11
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
MAXIM INTEGRATED PRODUCTS MAX9374AEKA+T DIFF LVPECL-TO-LVDS TRANSLATOR, SOT-23This is a DIFF LVPECL TO LVDS TRANSLATOR, SOT 23 product from MAXIM INTEGRATED PRODUCTS with the model number MAX9374AEKA+TProduct details Operating Temperature Min 40C Output Current Logic Type Level Translator Operating Temperature Max 85C Propagation Delay 250ps No. of Pins 8Pins Logic Case Style SOT 23 Product Range Automotive Qualification Standard Supply Voltage Min 3V No. of Inputs 2 Packaging Cut Tape Supply Voltage Max 3. 6V MSL MSL 1
This is a DIFF LVPECL-TO-LVDS TRANSLATOR, SOT-23 product from MAXIM INTEGRATED PRODUCTS with the model number MAX9374AEKA+TProduct details
| Operating Temperature Min | -40°C |
| Output Current | - |
| Logic Type | Level Translator |
| Operating Temperature Max | 85°C |
| Propagation Delay | 250ps |
| No. of Pins | 8Pins |
| Logic Case Style | SOT-23 |
| Product Range | - |
| Automotive Qualification Standard | - |
| Supply Voltage Min | 3V |
| No. of Inputs | 2 |
| Packaging | Cut Tape |
| Supply Voltage Max | 3.6V |
| MSL | MSL 1 - Unlimited |
Other details
| Brand | MAXIM INTEGRATED PRODUCTS |
| Part Number | MAX9374AEKA+T |
| Quantity | Each (Supplied on Cut Tape) |
| Technical Data Sheet EN |
All product and company names are trademarks™ or registered® trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them. Image is for illustrative purposes only. Please refer to product description.
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
4.9 ★★★★★
Based on 1408 reviews
Sort
Product Reviews
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 16, 2019
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript.
Great book.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 10, 2025
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on April 19, 2025
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 5, 2025
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents.
What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 17, 2025