SKU: 67954005793

Tamburo TB UNIKA520FW UNIKA Series 5-piece Wood Shell Pack with Snare Drum and 20" Bass Drum (Fantasy White)

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Description

Tamburo TB UNIKA520FW UNIKA Series 5-piece Wood Shell Pack with Snare Drum and 20" Bass Drum (Fantasy White)Over the course of more than 25 years of business, the cornerstone of TAMBUROs creations has always been innovation. Both in its use of materials and in its creation of revolutionary construction techniques that succeed in satisfying a range of drummers in search of their own sound. Today, thanks to our new UNIKA series, we have reached another milestone, creating an instrument that is easy to tune, powerful and versatile. featuring a strong structure

Over the course of more than 25 years of business, the cornerstone of TAMBURO’s creations has always been innovation. Both in its use of materials and in its creation of revolutionary construction techniques that succeed in satisfying a range of drummers in search of their own sound. Today, thanks to our new UNIKA series, we have reached another milestone, creating an instrument that is easy to tune, powerful and versatile. featuring a strong structure that is easy to transport. Our UNIKA drumkit is the product of the latest technology and materials – a 100% Made-in-Italy project.

TECHNOLOGY AND PROCESSES

THE SHELL

Our shells consist of a “sandwich” structure, with two strong HPL (High Pressure Laminate) layers that have a minimum thickness of 0.8 mm to 0.9mm. The shell’s thickness depends on the type of color and finish. These elements are connected by an internal band made from three alternate one-millimeter wooden layers. This particular structure lends considerable strength and stability to the shell. The rigid, lightweight structure, its perfect point of contact with the skin (Start Point), together with a new ST (Strong Traction) lug, are key to its extraordinary tuning range. In addition to providing a strong anchor point for the lugs, the internal HPL layer (a material not previously used to make drums) makes the shell waterproof, thus preventing deterioration over time.

THE ST LUG (patent pending)

Our new TAMBURO ST (Strong Traction) lug stands out due to its innovative design, which features two tie rods connected by a tube. Its unique structure allows you to achieve a sensitive, fluid and stable tension between the skins. This also ensures maximum mechanical hold (approx. 3500kg) with each full key turn. The lightweight lug consists of parts that have been specifically designed to aid high mechanical resistance.

SNARE STRAINERS

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.

HOOPS

Our hoops are made with an internal and external HPL (High Pressure Laminate) lining, which defines both finish and color. Twelve layers of internal beech are attached in the same direction, using a special PU glue. This is how a rigid drum hoop with strong mechanical properties is created. Boasting a thickness of just 8mm.

FLOOR TOM BRACKET

Lightweight alloy chrome die cast lug with side Tamburo “butterfly” locking screws. The legs can be fixed in place quickly and securely. The lug has a soft , anti-vibration rubber seal. Its shape and limited size helps to keep the drum in its case.

DRUM LEGS

Thanks to their characteristics, our drum legs offer stability and ease when positioning drums. Strong and lightweight, they’re attached to the shell via four anchor points. Our bass drum leg provides the drummer with a customizable, stable position.

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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.
                                    • To process your return/exchange, please contact us at [email protected]
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                                    SKU: 67954005793

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                                    4.9 ★★★★★
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                                    Verified Purchase
                                    Par
                                    Louisville, 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
                                    Alexandria, 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
                                    Birmingham, 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
                                    Carnegie, 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
                                    Omaha, 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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