SKU: 71749478677
herbicide gel

herbicide gel 99% Organic Aloe Vera Gel Refill, 64oz Moisturizer

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Description

herbicide gel 99% Organic Aloe Vera Gel Refill, 64oz MoisturizerNaturSense 99% Organic Aloe Vera Gel. Our product is the purest aloe skincare product available. Organically grown, harvested, cold pressed and bottled in the USA. ECO FRIENDLY 64. 2 FL Oz bottle with convenient pump dispenser Perfect for Hair Scalp Face Dry Sensitive Skin Acne Sunburn Organic formula with the same trusted ingredients! Organic: 99% organic aloe vera juice the purest aloe skincare product available, grown without pesticides,

NaturSense 99% Organic Aloe Vera Gel. Our product is the purest aloe skincare product available. Organically grown, harvested, cold-pressed and bottled in the USA.

🌿 ECO-FRIENDLY 64.2 FL Oz bottle with convenient pump dispenser 🌿
Perfect for Hair • Scalp • Face • Dry/Sensitive Skin • Acne • Sunburn
Organic formula with the same trusted ingredients!
🏆 Organic: 99% organic aloe vera juice - the purest aloe skincare product available, grown without pesticides, herbicides, or synthetic fertilizers.
💧 Superior Quality: Cold-pressed, ultra-filtered aloe vera juice with minimal plant-based thickener. Silky consistency that absorbs without sticky residue.
🌱 Maximum Potency: Experience the highest concentration of essential vitamins, minerals, proteins, and enzymes for optimal skin and hair benefits.
♻️ Eco-Friendly Size: 64.2 oz bottle refills your 12 oz bottle over 5 times, reducing waste and maximizing value for DIY skincare projects.
🛡️ Natural Protection: Effectively guards against unwanted environmental agents while maintaining anti-inflammatory and antioxidant properties.
⭐ Made in USA: From farm to formulation to filling, the entire process takes place in facilities in the United States.

🧴 For Skin Care

Daily Use: Apply morning and evening to face and body for hydration.

Targeted Relief: Soothe sunburn, insect bites, and skin irritations.

Sensitive Skin: Perfect for all skin types, including radiation-treated skin.

Note: Thin consistency due to minimal plant-based thickeners. Reapply as needed.

💇 For Hair Care

Pre-Shampoo: Use as scalp treatment before washing to address dandruff and itchiness.

Conditioning: Apply after shampooing for added moisture and shine.

Styling: Use as a light, natural hair gel. Leave in or rinse out based on your needs.

Scalp Health: Nourishes scalp and promotes healthy hair growth.

NaturSense Aloe Vera Gel

Pure, organic aloe vera gel that works for every skin type and so much more

Not Just For Sunburn

Our Organic aloe vera gel is a universal skin champion, tailor-made to bless every skin type with its soothing embrace! From the driest to the oiliest complexions, it balances, hydrates, and revives, ensuring everyone gets a slice of its magic. No matter your skin concern, aloe's multi-use prowess is here to rescue and rejuvenate!

Shiny, Manageable Hair and Nourished Scalp

Infuse every strand with unparalleled moisture and shine! Its deeply nourishing properties nurture the scalp, addressing dandruff and itchiness. Witness your tresses transform, basking in strength, softness, and vitality!

Cool Radiation-Treated Skin

Since its introduction in 2015, many customers have reached for our product to comfort their radiation-treated skin. Trust in the supporting touch of NaturSense Aloe to stand by you, with our dedication to your skin's condition and resilience through every phase of treatment.

Our Mission: To Earn and Keep Your Trust

At the heart of our family business is a deep-rooted commitment to honesty, quality, and integrity. Every product we craft and every interaction we have is a testament to our unwavering dedication to earning your trust. We cherish the bonds we build with our customers, and promise to uphold the values that make our family business truly special in every endeavor.

Why Choose NaturSense?

Quality, value, and versatility in every bottle

NaturSense Aloe is Organic

Our organic product assures that you're getting a product grown without pesticides, herbicides, or synthetic fertilizers. With NaturSense, you have a gel that's as close to nature as possible, and you're making a statement that you value the utmost quality in your skincare.

Our 64.2 oz Size = 5 1/3 Bottles of our 12 oz Size

Purchasing our aloe vera gel in this convenient 64.2 oz bulk size offers a cost-effective approach. Whether refilling your 12 oz or travel size bottles, or using quantities for your own skin care formulations, you can minimize your environmental footprint and maximize your savings.

All the Properties of Aloe You're Looking For

Our organic aloe vera gel is valued for being moisturizing and calming. Its natural composition is ideal for many skin concerns. Regular application can also aid in maintaining skin hydration, promoting a more balanced and youthful-looking complexion. It's also great for hair and scalp.

Convenient Size for Your DIY Projects

You want a consistent and quality base for your DIY projects, and our 64.2 oz size is a great solution! It offers a better value over time, reducing the need for frequent repurchases. Having a substantial supply on hand also simplifies the process, allowing for uninterrupted crafting, experimentation and more fun for you!

What's Inside

A short, transparent ingredient list — nothing hidden, nothing unnecessary

🌿 Organic Aloe Barbadensis (Aloe Vera) — 99%: Cold-pressed and superior filtered for maximum potency. The vitamin-rich, mineral-rich, and enzyme-rich heart of every bottle.
🌱 Xanthan Gum: A plant-based thickener that gives the gel its smooth, silky feel — no synthetic fillers.
⚖️ Citric Acid: A naturally derived pH stabilizer that keeps the formula balanced and skin-friendly.
🍊 Ascorbic Acid (Vitamin C): Helps preserve the gel's freshness and protect its natural potency.
🛡️ Potassium Sorbate: A gentle, food-grade preservative recognized by the FDA as Generally Recognized As Safe (GRAS).

🌿 NaturSense Brand Promise 🌿

At the heart of our family business is a deep-rooted commitment to honesty, quality, and integrity. Since 2015, we've been bringing you the very best in organic skincare. We're here to support you with any questions or product assistance you may need.

  • ORGANIC - More than just containing organic ingredients, NaturSense Aloe Gel is made with certified organic aloe!
  • SAME GREAT FORMULA, NOW IN ECO-FRIENDLY 64 OZ SIZE - Refill your 12 oz bottle over 5 times! Perfect for DIY skincare projects!
  • UNLIKE DRUGSTORE BRANDS loaded with harsh thickeners, undesirable compounds and little aloe, ours is 99% organic, cold-pressed, superior filtered aloe!
  • FANTASTIC DAILY MOISTURIZER - Our aloe absorbs into the skin without leaving a sticky or oily residue!
  • SOOTHES SUNBURNS, INSECT BITES AND IRRITATED SKIN - Perfect for sensitive skin and radiation-treated skin!
  • CONDITIONS HAIR AND SCALP - Addresses dandruff, itchiness, and promotes healthy hair growth!
  • INCLUDES ANTIOXIDANT VITAMINS A, C AND E - Maximum potency of essential vitamins, minerals, proteins and enzymes!
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: 71749478677

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4.4 ★★★★★
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Kirsten
Boise, US
★★★★★ 5
Holds a decent amount of jewelry!
Color: Carbonized Brown, Color: Carbonized Brown
I was quite impressed with this little jewelry box. Although it is on the smaller side, it utilizes every bit of the storage space available really well. I’d ultimately love to get a bigger armoire- as it is, this jewelry box contains what I wear most often, but I have a larger collection than this particular jewelry box can hold- my plan is to find a larger jewelry armoire that resembles what my mother had because I loved that one and then passed this one down to my daughter who loves it. For its size, it does absolutely hold a lot. I definitely underestimated how much it would hold. I love that there are drawers and well. I would love to see the ring area hinged so that I don’t have to reposition it when I’m done grabbing my rings, I think it’s a really cool, unique way to approach that particular area. I love that every little bit at this jewelry box is designed to have utility. I hate wasting space and time and I love good organization so it’s been really nice being able to pack as much as I can in there. The top opens up to space for earrings and other miscellaneous items. There are both open and more structured components. And the space for bracelets rotates, which is really nice- I didn’t realize that it rotated and I was a little bit worried that I was gonna constantly knock things down while I was reaching through or something. There is lots of room inside both doors for necklaces, and it fits a lot more than I thought it would. The wood stain is a really pretty kind of ashy natural stain- the sort of grey tint is really nice and it’s gorgeous. I’m not a huge fan of mirrors as far as the front goes, but I do have an artist in house who is really good at coming up with stuff for this, just a little ways to put art in your every day, so I’ll probably have her paint over. The jewelry box also doesn’t take much space up at all. While I am looking for something with a little bit larger footprint, I don’t necessarily want to waste a bunch of real estate in the meantime so I’m really pleased with how compact it is. This is a great little jewelry box - as I mentioned it doesn’t house all of my jewelry, but that’s because my collection is mostly heirloom and I don’t want to take it out from where it is right now. If it were larger, I would probably do so but for now it just houses my everyday items and a little bit extra. I think it’s great and I’m super happy with it!
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Reviewed in the United States on March 17, 2026
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Chelsea, US
★★★★★ 5
Excellent book, possibly currently unique in coverage of latest ideas
This book is possibly currently unique in its coverage of the latest ideas in the field of deep learning -- and it is a very convenient and good survey of fundamental concepts (linear algebra, optimization, performance metrics, activation function types), different network types (multi-layer perceptron, convolutional neural networks, and recurrent neural networks), practical considerations (data set, training and validation, implementation), and applications (comments on existing real-world/commercial uses). The final 235 pages of the content portion of the book is dedicated to topics in "Deep Learning Research", and these topics are truly at the current frontier. Another reviewer said that one could gain the same knowledge of cutting-edge research by reading all of the latest papers (from academia and industry), but the "research" section of this book offers the following: Selection of the most notable research by the very experienced authors of the book, and collection of similar research in to a broader discussion of themes, and the additional insights. The book covers very advanced and new ideas currently being explored, and it is very nice to be able to have a consistent and coherent presentation of all of those ideas. However, the book is also packed with valuable observations and pointers about more basic aspects of deep learning implementations and practices -- and such commentary is in depth and includes substantial analysis and mathematical derivation (in an intuitive presentation that often includes graphs illustrating the phenomenon). As someone with an intermediate level of knowledge and experience of neural networks, I am really grateful for this book, because seems like the ideal resource for learning cutting-edge ideas and practices, with context. The book has excellent scope and depth, and I am confident that anyone with a solid background in linear algebra, calculus, statistics, and general machine learning, and basic neural networks (multi-layer perceptrons) will find this book to be very exciting and perhaps unique in its ability to take the reader to the next level and a new frontier. I was personally excited to learn about the idea of representing the dependencies of intermediate quantities by directed graphs, and how this can be used to perform calculations for recurrent neural networks efficiently. And I think the long chapter on recurrent neural networks is very helpful. Having said all of this, I think only people with significant working knowledge and experience with neural networks and mathematics -- people whose academic or professional focus has been neural networks for at least a year or two -- would benefit from this book. This book answers a lot of the deeper questions that one is likely to have while developing a solid understanding of the fundamentals, and that's one of the book's tremendous values, but this book assumes an understanding of the fundamentals (but does briskly cover the basics). I think this book is a perfect follow-up book for the excellent book "Neural Network Design (2nd edition)" by Hagan, Demuth, Beale, and de Jesus, and I highly recommend the latter for gaining the solid background needed to have a thrilling experience with the "Deep Learning" book. In summary, I am very glad this "Deep Learning" book was written, and I think the "Deep Learning" book will be a great benefit to a lot of people, and to the evolution of the field.
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Reviewed in the United States on April 18, 2017
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Zygerian99
Natrona Heights, US
★★★★★ 5
The definitive guide to becoming a researcher in the field
Format: Hardcover
This is not a coding book. I see a lot of negative reviews around the expectation that this book would teach the reader how to quickly build machine learning systems and write code. This book is not for that audience. If you just want to build applications, don't worry about how deep learning works. It's akin to needing to understand how an engine works just to drive a car. If you are looking for a coding resource, try: https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_4?keywords=machine+learning+tensorflow&qid=1579608765&sr=8-4 . And even with that book, the material still goes far beyond what you need - use it as a light reference. I bought this book as an aspiring machine learning researcher, and towards that end, it is the best resource available in print (still true as of 2020). For instance: The first 5 chapters are timeless. These are things that were mostly established 20 or 30 years ago and beyond and are mostly STEM fundamentals at this point. There are whole textbooks dedicated to each of those chapters, but the authors provide a quick refresher and overview of probably 80% of what you'll encounter in deep learning. If you haven't previously learned each of these subtopics, you'll probably want to study them individually since they are the key to innovating (linear algebra, probability & stats, numerical computation, machine learning fundamentals). Chapters 6 thru 9 are the foundation of deep learning. We're about 12 years into seeing rapid change in the deep learning space, yet all of these principles and techniques still hold (many recent innovations are still relying on Convolutional models in 2020, which is the most layered/complex topics in those chapters). Therefore, I'd wager that these chapters are also fairly stable knowledge that is worth internalizing if you want to be deeply involved in the future of machine learning. Chapters after 9 are mostly experimental topics, and many of them are already the wrong strategies for optimal results. But there are interesting ideas in here that you'll often encounter in the wild, so it's good exposure to various topics. But probably not worth much of your time. And lastly, there is good history in here from people who know the space intimately. It's a good way to piece together the developments and learn the lexicon of deep learning so you can have intelligent conversation with experts.
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Reviewed in the United States on January 21, 2020
S
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Shannon
Carnegie, US
★★★★★ 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
W
Verified Purchase
William P Ross
Dallas, US
★★★★★ 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

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