SKU: 51612267507
sterilizing soil for indoor plants

sterilizing soil for indoor plants 100% Organic Indoor Plant Potting Soil Mix — Nutrient Rich, Well-Draining Living Soil Blend

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Description

sterilizing soil for indoor plants 100% Organic Indoor Plant Potting Soil Mix — Nutrient Rich, Well-Draining Living Soil BlendBreathable, 100% organic soil for thriving houseplants. Our thoughtfully blended mix combines 100% organic coco coir, biochar, perlite, and compost to create the ideal growing environment every plant parent dreams of excellent aeration, steady nutrition, and reliable drainage without drying out. No more worrying about overwatering or root rot this mix promotes lush foliage, robust root systems, and effortless watering for all your green companions.

Breathable, 100% organic soil for thriving houseplants.

Our thoughtfully blended mix combines 100% organic coco coir, biochar, perlite, and compost to create the ideal growing environment every plant parent dreams of — excellent aeration, steady nutrition, and reliable drainage without drying out. No more worrying about overwatering or root rot — this mix promotes lush foliage, robust root systems, and effortless watering for all your green companions.

Why You'll Love It:

100% organic formula with optimal moisture retention and airflow to promote healthy root development
Enriched with coco coir, biochar, and compost for long-lasting, nutrient-rich plant growth
Ideal for most houseplants, including pothos, philodendron, calatheas, and more
Easy-to-use, resealable ziplock bag keeps soil fresh and mess-free between uses
Custom blended by a small family business in Oregon using clean, locally sourced, sustainably sourced ingredients

How to Use:

1. Sanitize and prep your pot with adequate drainage holes.
2. Add 2–4 inches of soil to the base.
3. Remove the plant from its old container and gently loosen roots.
4. Place your plant and backfill with Premium Potting Soil.
5. Lightly press and water thoroughly until moisture runs from the bottom.
6. Reapply as needed or when repotting.

What's Included:

  • 8 Quarts / 7.57 Liters / 0.26 Cubic Feet of Indoor Plant Soil
  • Resealable bag for clean storage
  • Blend of sandy loam, coco coir, biochar, green compost, sphagnum peat, perlite & more

Backed by Real Plant People

This soil mix is part of an integrated plant care system trusted by thousands of home gardeners. It’s the perfect upgrade from generic soil mixes—helping your houseplants thrive season after season.

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SKU: 51612267507

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4.0 ★★★★★
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William P Ross
Birmingham, 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.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
West Palm Beach, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Lake Worth, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
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Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Belleville, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
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Reviewed in the United States on May 15, 2018
S
Verified Purchase
Stergios Papadimitriou
Fort Morgan, US
★★★★★ 5
The classic textbook on Deep Learning
Format: Hardcover
Deep Learning is the promising direction towards general purpose effective artificial intelligence. There is an explosion of fruitful research in recent years and a lot of applications pursued mainly from technology giants as Google, Amazon, etc. and outstanding research institutions. The book "Deep Learning " by Ian Goodfellow, Yoshua Bengio, Aaron Gourville, is an excellent piece of work. They manage to present rather difficult things in an understandable manner. The theoretical presentation is outstanding typical of "classic" books. Also, the book stays close to the practical applicability of all the methods and discusses applications extensively. There are a lot of other useful books on deep learning that follow a more practical approach by focusing on a particular deep learning software package, but this one book is certainly much more essential since it provides the required theoretical background in order to be able to do serious work on deep learning. I consider the book as "must have" for anyone that works on deep learning either in an academic or in an industrial environment.
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Reviewed in the United States on August 25, 2018

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