SKU: 94003730998

Lindy Fralin Pure P.A.F. Bridge Humbucker Raw Nickel

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Description

Lindy Fralin Pure P.A.F. Bridge Humbucker Raw NickelMaker: Fralin Pickups Model: Pure P. A. F. Humbucker, Stock Output, Gibson Spacing, 3 Conductor Condition: New Description: Experience what a humbucker should really sound like and get inspired by the Pure P. A. Fs beautiful tone. Lindys favorite humbucker, the Pure P. A. F. is a 50s P. A. F. clone, using real Butyrate Bobbins and all USA Made parts. Featuring a clean, clear tone with incredible versatility and dynamics and expertly crafted using 100%

Maker: Fralin Pickups

Model: Pure P.A.F. Humbucker, Stock Output, Gibson Spacing, 3-Conductor

Condition: New

 

Description: 

Experience what a humbucker should really sound like and get inspired by the Pure P.A.F’s beautiful tone. Lindy’s favorite humbucker, the Pure P.A.F. is a 50’s P.A.F. clone, using real Butyrate Bobbins and all USA-Made parts. Featuring a clean, clear tone with incredible versatility and dynamics and expertly crafted using 100% USA-Made materials, we guarantee the Pure P.A.F. will inspire you for years to come.

Are you ready to cut through in the mix? The Lindy Fralin-designed Pure P.A.F. is our best-selling humbucker. Based on the specifications of the original 50’s Gibson® P.A.F. pickups, this model features a clean, articulate tone that’s incredibly versatile.

The Pure P.A.F. is a lower output humbucker, which is more dynamic and expressive than higher output pickups. It’s more articulate and cleaner than our Modern P.A.F., but beefier than our P-92. Lindy’s passion for the sound of vintage 50’s humbuckers led us down the road to design and create the Pure P.A.F., and it’s easy to see why – this pickup sounds incredible.

FEATURES:

  • Our Best-Selling Humbucker – low output, vintage tone
  • Original Gibson PAF® specifications: low output, with modern clarity
  • Clean and clear, smooth grind and a sharp attack
  • USA-made Alnico 2 Magnets for vintage tonal balance and output
  • Compensated Overwound Bridge for even volume across all pickups
  • Hand-wound with our “Sectioning” technique for unique, dynamic tone
  • Hand-built for unrivaled quality control
  • 10-Year Warranty on manufacturing defects

Sound

How does it sound? Clean and articulate!

The Pure P.A.F. stays clean and features a late break-up and a smooth grind. This pickup is perfect if you’re trying to restore life to your guitar. Don’t let the term “vintage” fool you – you’ll find that it’s loud and versatile enough to play with modern-voiced pickups; it just features more clarity than modern humbuckers.

Built with USA-Made AlNicCo II and 42-gauge Plain Enamel wire, the Pure P.A.F. pickup is a gateway to instant vintage tone. When playing without distortion, you’ll find that this pickup sings what you put into it: it’s dynamic and warm. Highs are accentuated with a medium attack. With distortion, you’ll find that the grind is nice and smooth.

Our manufacturing process allows us to achieve unparalleled quality control. When Lindy designed this pickup, he wanted it to be as close to the originals as possible. Pure P.A.F.’s consist of USA-Made Butyrate bobbins, baseplates, magnets, and wire. We wind each pickup by hand, one at a time, using our proprietary “Sectioning” technique. Doing this gives the pickup a sweet, clear tone, reminiscent of the early Gibson Humbuckers/

Finally, we assemble each pickup one at a time, by hand, which allows us to achieve unbeatable attention to detail. After assembly, we wax-pot the pickup to prevent microphonics and preserve the pickup for years to come.

Tech Specs

SPECIFICATION VALUE
Neck Ohm Reading (Stock): 7.5K
Bridge Ohm Reading (Stock): 8K
Neck Polarity: Reversible with 3-Conductor or 4-Conductor Lead
Bridge Polarity: Reversible with 3-Conductor or 4-Conductor Lead
Magnet: USA-Made Alnico 2
Wire: USA-Made 42-Gauge Plain Enamel
Bobbin Material: USA-Made Butyrate
Baseplate Material: Nickel Silver
Cover Material: Nickel Silver
Slug / Pole Piece Material: Steel
Recommended Pot Value: 500K*
Baseplate Leg Depth: 6mm

* You can experiment with pot values for a different tone. This pickup will sound dark and warm on 250K pots

 

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SKU: 94003730998

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Par
West Palm Beach, US
★★★★★ 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.
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Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
West Palm Beach, US
★★★★★ 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.
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Reviewed in the United States on February 26, 2022
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Verified Purchase
Amazon Customer
Lake Worth, US
★★★★★ 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
K
Verified Purchase
Kindle Customer
Pawtucket, US
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
T
Verified Purchase
Tommy Jonsson
Cuba, US
★★★★★ 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

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