SKU: 94373384396

2015 Fender Classic '69 reissue Blue Flower Telecaster Made in Japan

$601.63 $668.48
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Description

2015 Fender Classic '69 reissue Blue Flower Telecaster Made in JapanMaker: Fender Model: '69 Blue Flower Telecaster Reissue Condition: Excellent Description: Here for your consideration is a 2015 MIJ Fender Classic '69 reissue Blue Flower Telecaster in excellent condition! This one appears to have not seen much use showing only some very light surface marks and only the lightest amount of fret wear. Hardware shows some very light signs of wear but is overall very clean. This one plays like butter and with its classic

Maker: Fender

Model: '69 Blue Flower Telecaster Reissue

Condition: Excellent

 

Description: 

Here for your consideration is a 2015 MIJ Fender Classic '69 reissue Blue Flower Telecaster in excellent condition! This one appears to have not seen much use showing only some very light surface marks and only the lightest amount of fret wear. Hardware shows some very light signs of wear but is overall very clean. This one plays like butter and with its classic 60's Flower finish is a lean, mean, super clean psychedelic machine. Has been fully inspected and set up by our tech and ready for a new home. Includes gig bag. See below for a full list of specs.

Weight: 6lbs 8oz

Neck Profile: Slim "C"

Neck Thickness: 1st fret .806", 12th fret .943"

Fretboard Radius: 7.25"

Nut Width: 1 5/8"

Pickup Values: Neck 6.5k, Bridge 5.8k


From Fender:

Inspired by the burgeoning psychedelic music scene, this dazzling guitar reflects the exciting, experimental times of the late 60s. Built on the classic 1969 Telecaster, and delivers unmistakable Fender sound.

The '69 Flower Telecaster has all the Tele twang and bite you've grown to love, courtesy of the pair of vintage-style single-coil Tele pickups. The traditional control complement--master volume, tone and a three-position pickup switch--shape the pickups' voice to match your sonic vision. The American Vintage three-saddle string-through-body bridge offers chrome barrel saddles for classic Fender tone. Topped by a vintage-accurate 7.25"-radius maple fingerboard, the comfortable "Slim C"-shaped one-piece maple neck hosts 21 vintage frets and a synthetic bone nut.

Body
Basswood
Body Finish
Gloss Polyester
Body Shape
Telecaster®
Bridge
3-Saddle Vintage-Style Strings-Through-Body Tele® with Chrome Barrel Saddles
Bridge Pickup
Vintage-Style Single-Coil Tele®
Color
Blue Flower
Commodity Code
[object Object]
Configuration
SS
Control Knobs
Knurled Flat-Top
Controls
Master Volume, Master Tone
Country Of Origin
JP
Dimensions
4.00x15.00x45.50 IN
Fingerboard
Maple
Fingerboard Radius
7.25" (184.1 mm)
Fret Size
Vintage-Style
Hardware Finish
Chrome
Model Name
Classic 69 Tele, Maple Fingerboard, Blue Flower
Neck Finish
Gloss Polyester
Neck Material
1-Piece Maple
Neck Material
1-Piece Maple
Neck Pickup
Vintage-Style Single-Coil Tele®
Neck Shape
Slim "C"
Number of Frets
21
Nut Material
Synthetic Bone
Nut Width
1.650" (42 mm)
Orientation
Right-Hand
Pickguard
None
Pickup Configuration
SS
Pickup Switching
3-Position Blade: Position 1. Bridge Pickup, Position 2. Bridge and Neck Pickups, Position 3. Neck Pickup
Position Inlays
Black Dot
Neck Material
Maple
Neck Shape
C Shape
Pickups
Vintage-Style
Scale Length
25.5" (648 mm)
Series
Made in Japan Classic
String Nut
Synthetic Bone
Tuning Machines
Gotoh® Cast/Sealed
Shipping Notes
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SKU: 94373384396

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A
Verified Purchase
Amazon Customer
Massapequa, 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
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Kindle Customer
Carnegie, 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
Port Orchard, US
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
M
Verified Purchase
Moses Kayanda
Fort Morgan, US
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid. I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets. As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before. I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
G
Verified Purchase
Gabe Rigall
Omaha, US
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt. PROS: - Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way. - Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops. - Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages. - Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them. - PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly. CONS: - Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste. - Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022

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