SKU: 19911699707

Tamburo TB VLSD1465YW VOLUME Series Seamless-Acrylic Snare Drum (Yellow) - 14" x 6.5"

$207.76 $230.84
Save 10%
No.2 Bestseller on sm10m.ch >

Pay in installments of $57.71 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Aug 23 - Aug 28

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Tamburo TB VLSD1465YW VOLUME Series Seamless-Acrylic Snare Drum (Yellow) - 14" x 6.5"The VOLUME Series snare drums are made from methacrylate that is 3. 5mm in thickness, they are not only superlight in weight but provide an incredible range of tuningsuiting everything from light jazz to heavy metal. The VOLUME snare drum is available in four different finishes. TECHNOLOGY AND PROCESSES THE SHELL The Volume acrilic shell born thanks to a research related to how is possible uses the methacrylate to make a perfect shell for drums. So,

The VOLUME Series snare drums are made from methacrylate that is 3.5mm in thickness, they are not only superlight in weight but provide an incredible range of tuning—suiting everything from light jazz to heavy metal. The VOLUME snare drum is available in four different finishes.

TECHNOLOGY AND PROCESSES

THE SHELL

The Volume acrilic shell born thanks to a research related to how is possible uses the methacrylate to make a perfect shell for drums. So, all the changing was made on the material to looking for the right way to make a shell, with a good sound caracteristics. The VOLUME shells haven’t the joint glue point and the thikness and the diameter size are made to produce a “afono” shell with an amazing sounds. The shell thickness moves from a minimum of 3 mm to a maximum of 4 mm. Related to Tamburo Philosophy the Bearing Edge is replaced by the Perfect Curve that follow the drum head curve.

DRUM HOOPS

Lightweight 2.3 triple flange hoops that provide low, defined harmonics.

SNARE STRAINER

Our fused block lug allows for the fluid, precise adjustment of strainer tension. A small magnet is included in the mechanism to ensure stability and grip over time.

  • Thickness: 3.5 mm
  • Diameter: 14”
  • Depth : 6.5”
  • Triple Flange Regular hoop
  • 10 Tension rods
                                                    Shipping Notes
                                                    • Free Standard Shipping on $100+ Orders to the USA.
                                                    • Except Preorder products are shipped in 48 hours.
                                                    • Delivery to the USA:
                                                    1. 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
                                                    SKU: 19911699707

                                                    Discover Niche Categories That Outsell

                                                    Top-Converting Item to Boost Your Average Order

                                                    4.3 ★★★★★
                                                    Based on 29 reviews
                                                    Sort
                                                    Highest Rating
                                                    Newest First
                                                    Oldest First
                                                    Product Reviews
                                                    P
                                                    Verified Purchase
                                                    Par
                                                    Whiting, 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
                                                    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.
                                                    WAS THIS REVIEW HELPFUL?YesReportShare
                                                    Reviewed in the United States on February 26, 2022
                                                    A
                                                    Verified Purchase
                                                    Amazon Customer
                                                    Natrona Heights, 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
                                                    Whiting, 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
                                                    Draper, 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

                                                    recommand products

                                                    Wilwood Forged Dynalite P/S Park Brake Kit Drilled Red Big Ford 2.36in Offset Currie Blank - 140-7142-DR
                                                    598.47
                                                    Wilwood Forged Dynalite P/S Park Brake Kit Mopar/Dana 2.36in Off w/Snap Ring Brng - 140-7144
                                                    529.72
                                                    Wilwood Forged Dynalite P/S P-B Kit Drilled Polished Chevy 12 Bolt w/ C-Clips - 140-7141-DP
                                                    697.53
                                                    Copper Heat Shade with Marble
                                                    428.40
                                                    160mm Non-Stick Brioche Mould
                                                    15.00