SKU: 7681341989

Mr. Peanut's Gold Series Big Apple Double Expandable Pet Carrier

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Description

Mr. Peanut's Gold Series Big Apple Double Expandable Pet CarrierThe Gold Series is the ultimate travel carrier for dogs and cats! Whether by car, airline, or on foot, its a top choice of pet professionals worldwide. Designed for travel, its flexible height let's it compress to fit under most airline seats while still providing structure and space for your pet as well as an expandable port. Created with premium features for comfort and convenience, the Gold Series is a smart choice for every pet owner. The Gold

The Gold Series is the ultimate travel carrier for dogs and cats! Whether by car, airline, or on foot, it’s a top choice of pet professionals worldwide. Designed for travel, its flexible height let's it compress to fit under most airline seats while still providing structure and space for your pet as well as an expandable port. Created with premium features for comfort and convenience, the Gold Series is a smart choice for every pet owner.

The Gold Series Big Apple model is slightly longer than the standard sized model, It is designed for those pets where a smaller length is simply not an option.
  • Premium Brand Auto Self Locking Zippers for Safety and Eliminating the need for fragile clasps as the tote cannot be pushed open by your pet from the inside
  • Faux Fleece Padding with Plywood Base Insert for Additional Support & Weight Handling
  • Airline Capable , best fit for pets approximately less than 18" in length while laying down. Keep in mind the interior of any bag is less then than the exterior due to fabric and padding thickness.
  • Recommended for Pets Up to 25lbs
  • Weighs only 3.9lbs
  • Open Air Large Mesh Windows on Top and Sides 
  • Fabric Roll Away Privacy Cover with Top Loading Zippered Opening & Roll Down Velcro Mesh Window Cover
  • Luggage Strap
  • Zippered Mesh Pocket for Storing Treats, Meds, Papers
  • Padded Shoulder Strap with Thick Metal Connectors for Additional Safety,
  • Hand Carry Handle 
  • Wipe Down Composite Nylon Soft-Sided Pet Carrier w Vegan Leatherette Highlights
  • Name Tag Holder
  • Leash Tether
  • Safety Seat Belt Attachments
  • Leak Proof Design and Materials 
  • Mr. Peanut's Cool Logo Storage Pouch Included
  • MR. PEANUT'S is a USA based, Family owned business and a proud sponsor of the Pay a Shelter Pet Forward Program

Free Gift - All purchases of a pet carrier(s) from Mr. Peanut’s direct site receive a complimentary set of 4 Premium Gel Pee Pads and a collapsible travel bowl for each. (Excludes Amazon Buy With Prime purchases)

Dogster Magazine Review 

Many ask what is the difference between the models, and especially between the most popular Gold and Platinum Series. I do have a FAQ page which has some more specifics on all the models, but the primary difference between these two series is that the Gold Series models all use a strengthened 600D nylon fabric that allows for maximum pliability while still retaining its structure, whereas the Platinum Series models use a lighter weight, wrinkle free 300D nylon. Neither is superior to the other, as each borrow features from the other, but they are mostly different in aesthetics.

HOW TO MEASURE YOUR PET - I always recommend to measure your pet while comfortably laying down, as this is the typical position during flight time. Keep in mind all of my airline capable bags are designed with pet safety and comfort as the priority, and then by airline under seat requirements, so sizing is limited by that criteria. In addition to the sizing guidelines and images shown here, many users have found it helpful to view the Instagram feed, @mrpeanutspetcarriers, where there are contributions with pets of every size and virtually every model.

Be Sure to acclimate your pet as much as possible to a new carrier in a home environment. You never want their first adventure out to be to a stressful airport or veterinarian. Let your pet come to appreciate the carrier as a safe home away from home. 

    Recommended Additions:
    Pet Potty Pads
    Collapsible Bowls
    Portable Pet Water Bottle

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      SKU: 7681341989

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      4.4 ★★★★★
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      Walter Echo-Hawk, author of THE SEA OF GRASS.
      Lake Worth, US
      ★★★★★ 5
      Native American history at its best!
      Format: Hardcover
      Kent Blansett's engrossing story about the life & times of the famed Mohawk activist Richard Oakes is Native American history at its best. I appreciated the well-written context provided about the birth, growth and impact of the Red Power Movement and the pivotal role that social justice activism played in the rise of modern Indian nations in the United States today. This scholarly work helps us understand modern Native America and is a "must-read" for every Native American Studies student and scholar, as well as readers interested in important American social justice movements.
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      Reviewed in the United States on April 1, 2019
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      Verified Purchase
      Par
      Port Orchard, 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.
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      Reviewed in the United States on December 20, 2024
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      Richard Hackathorn
      Battle Creek, 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.
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      Reviewed in the United States on February 26, 2022
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      Amazon Customer
      Waukegan, 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
      Battle Creek, 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

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