SKU: 33449807624

Michelin Cyclocross Mud Green/Skin Classic 700 x 30c Cyclocross Folding Tyre

$45.90 $51.00
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Description

Michelin Cyclocross Mud Green/Skin Classic 700 x 30c Cyclocross Folding TyreOriginal tyre in production from the 1990s to the 2000s Thoroughly checked over Worldwide shipping Michelin Cyclocross folding tyre, hailing from France and in production from the 1990s to the 2000s. Made from rubber and weighing in at 393 grams. A fine choice for keeping your classic bike authentic, but also great for any other compatible bike too. The tyre's been thoroughly checked by one of our mechanics and graded as good condition, but do take a

✓ Original tyre - in production from the 1990s to the 2000s
✓ Thoroughly checked over
✓ Worldwide shipping

Michelin Cyclocross folding tyre, hailing from France and in production from the 1990s to the 2000s. Made from rubber and weighing in at 393 grams. A fine choice for keeping your classic bike authentic, but also great for any other compatible bike too.

The tyre's been thoroughly checked by one of our mechanics and graded as good condition, but do take a good look at the detailed photos so you can see the cosmetic condition before you buy.

NB: If mounted in the photos this is for illustrative purpose only, any wheels or rims shown are not included.

OVERVIEW

Condition - Good
Production Era - 1990s & 2000s
Country - French
Material - Rubber
Weight - 393 g
Stock Code - U-TY-F17C

TECHNICAL INFO

Size - 700 x 30c
Bike Type - Cyclocross
ISO Diameter - 622 mm (700c/28")

▼SHIPPING, TAXES & RETURNS

We've been safely sending orders around the world since 2010. There's a handy shipping calculator on the shopping cart page so you can see the cost of postage as soon as you've added it to your basket. Your order will be carefully packed and sent with tracking & insurance, we despatch most orders within 2-3 days but larger items and orders placed before the weekend can take an extra day or two to process.

We accept returns, please notify us within 14 days and ensure the item arrives back with us no later than 30 days after the order was received.

EU Customers – for orders under €150 (excluding shipping), VAT will be collected at checkout, but from 1st July 2026, due to new EU import regulations, there may also be a customs duty payable to the carrier. For orders over €150, all import fees will be payable to the carrier, with nothing collected at checkout.

USA Customers – import fees are now collected at checkout for all orders to the US, so there won’t be any surprise charges when your order arrives.

Other International Customers – local import fees may still apply, charged by your customs office or courier before delivery. These are not collected by us, so please check your local rates before purchasing.

Any applicable fees will appear at checkout.

▼HELP SECTION

Size - this is the manufacturer’s sizing and must match the size or your wheel. This can be confusing as tyres have had different sizing systems over the years, and there are many (sometimes conflicting) sizes available. For this reason it’s important to check the ISO diameter too for clarification, especially for 26” wheels.

Bike Type - the type of bike the tyre was designed to be used on. Road tyres will generally be narrow with minimal tread, touring tyres wider with a bit more grip in the tread, and cyclocross & MTB tyres wider still (especially the latter), with a much more pronounced tread pattern.

ISO Diameter - this relates to the diameter of the wheel rim at the point where the tyre is seated (bead seat diameter). This is a universal measurement, often displayed on tyres as 28-622 or similar, 28 referring to the tyre width and 622 being the ISO diameter in millimetres.

TPI - stands for threads per inch and refers to the thread count of the tyre casing. A high thread count usually means a more supple and lighter tyre, this can be anything as high as 320 tpi. We can’t always provide this information however, as it’s not always possible to know for sure.


Shipping Notes
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Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
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SKU: 33449807624

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4.8 ★★★★★
Based on 26 reviews
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P
Verified Purchase
Par
New York, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
R
Verified Purchase
Richard Hackathorn
Draper, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
A
Verified Purchase
Amazon Customer
Alexandria, 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
Chelsea, US
★★★★★ 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
T
Verified Purchase
Tommy Jonsson
Carnegie, 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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