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Description
HAKKO FM-2027 Soldering Iron / Conversion KitPlease refer to the User Manual for detailed specifications. Packing List *Soldering Tips Nozzles not included. To be purchased separately FM2027 01: Sleeve Assembly (Yellow), Connector Assembly, Heat Resistant Pad, Instruction Manual FM2027 02: Connector Assembly Only FM2027 03: Sleeve assembly, Connector assembly, Connecting cable, Heat resistant pad, Iron holder HAKKO FH 200, HAKKO 599B Tip cleaner Features Easy removal of sleeve assembly and tip
Please refer to the User Manual for detailed specifications.
Packing List
- *Soldering Tips/Nozzles not included. To be purchased separately
- FM2027-01: Sleeve Assembly (Yellow), Connector Assembly, Heat Resistant Pad, Instruction Manual
- FM2027-02: Connector Assembly Only
- FM2027-03: Sleeve assembly, Connector assembly, Connecting cable, Heat resistant pad, Iron holder HAKKO FH-200, HAKKO 599B Tip cleaner
Features
Easy removal of sleeve assembly and tip
Soldering iron in lock-type sleeve assembly. Simply press down on the lock release button and pull the sleeve assembly out! Both the sleeve assembly and soldering tip comes out easily for quick removal or tip change.
Easy and secure tip insertion
When the tip is inserted into the sleeve assembly, you should hear a 'click' sound. This means that the tip has been inserted securely.
Sleeve color variation
An addition of the green sleeve assembly to the current yellow, orange and blue allows the user to assign the color to a specific tip shape or size, making it easy to identify while working with multiple soldering irons.
Specifications
- Power consumption: 70W (24V)
- Temperature range: 200 to 450ºC
- Tip to ground resistance: <2Ω
- Tip to ground potential: <2mV
- Heating element: Composite heater
- Cord length: 1.2m
- Total length: 188mm (with 2.4D tip, without cord)
- Weight: 30g (with 2.4D tip, without cord)
Replacement Parts
| Part Number | Product Name |
| B3215 | Connector Cover |
| FH200-01 | Iron Holder with Cleaning Wire and Power Save Function |
| B2791 | Retaining Clip |
| 599B-02 | Tip Cleaner (Metal Wire Sponge) |
| 599-029 | Cleaning Wire |
| B3253 | Connecting Cable |
| B2300 | Heat Resistant Pad |
| B3216 | Yellow Sleeve Assembly |
| B3217 | Orange Sleeve Assembly |
| B3218 | Blue Sleeve Assembly |
| B3219 | Green Sleeve Assembly |
| A1519 | Cleaning Sponge (Replaces A1536) |
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- Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
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4.7 ★★★★★
Based on 27 reviews
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Product Reviews
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
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Reviewed in the United States on November 30, 2025
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning.
There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s.
The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read.
There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning.
The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique.
Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
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Reviewed in the United States on March 15, 2017
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry.
The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
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Reviewed in the United States on May 22, 2026
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff!
If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper.
As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture.
So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money.
The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018