SKU: 70018085881
thai pepper seeds planting

thai pepper seeds planting Thai Red Chili Hot Pepper

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Description

thai pepper seeds planting Thai Red Chili Hot PepperThai Red Chili Hot Peppers Heirloom Vegetable Seeds Caspsicum annuum Listing is for 1 packet with a minimum of 20 seeds Check out my tutorial on how to grow peppers from seed: https: youtu. be 9j74wQpahsA Check out my tutorial on how to transplant peppers for maximum production: https: youtu. be hqkwOP ci9M These Thai chili hot peppers are commonly used in Thai and Asian cuisine. They pack heat similar to habaneros (Scoville Scale <40,000 Units). They

Thai Red Chili Hot Peppers Heirloom Vegetable Seeds
Caspsicum annuum
Listing is for 1 packet with a minimum of 20 seeds

Check out my tutorial on how to grow peppers from seed: https://youtu.be/9j74wQpahsA
Check out my tutorial on how to transplant peppers for maximum production: https://youtu.be/hqkwOP-ci9M

These Thai chili hot peppers are commonly used in Thai and Asian cuisine. They pack heat similar to habaneros (Scoville Scale <40,000 Units). They are ready to harvest at 2-3 inches in length and when they turn a bright glossy red color. This particular variety is very productive and heat tolerant. 

Peppers are slow to germinate and slow to start growing to transplant size. I recommend to start seeds in pots/trays with a heat mat to speed up germination. Then start fertilizing weekly with half strength fertilizer once the first set of true leaves appear. Peppers are similar to tomatoes in that they like plenty of water and are heavy feeders. 

Peppers are perennial plants and can produce for several years if taken care of. In cold climates trim off all the leaves and bring in doors in a pot to over winter. Place back out doors once temperatures are nice and warm. In mild climates, pepper plants can be left out doors and might need to be covered on the coldest nights. 

Follow me on social media because I talk a lot about the same seed varieties I sell here in my shop and gardening tips. IG, YT, and TikTok: jerrasgarden. 

PLANTING
Germination: 10-14 days

Germination Temperature: Optimum soil temperatures are 75-85ºF

Seed Sowing Depth: 1/4” deep

Sowing: I highly recommended to start seeds in pots/trays as described above.

Harvest: Peppers can be harvested at the green stage all the way up to being fully yellow. For maximum sweetness harvest when the peppers have turned completely yellow.

 

Terms and conditions READ THIS PLEASE:
- Seeds will be shipped with no planting instructions to keep seed costs low to the buyer. Germination and plant care information is included in the description. I encourage each gardener to research specifics on how to be successful growing them. I also have lots of information on my TikTok, Instagram and YouTube channel all under the account name jerrasgarden. I started this shop to share my love of certain seed varieties and spread the knowledge of gardening. Please contact me if you cant find information or have additional questions.


- No returns or refunds once shipped. I am not responsible for lost or damaged packages caused by USPS. Since there are so many factors that affect germination and growing success, no refunds or exchanges are allowed once seeds have shipped. These are the same seeds I use in my personal garden so I can attest to their viability. Seeds are fresh season to season.


- Availability of seed in this shop varies depending on what I have decided to grow that season. With that said, please be advised that seeds are available in limited quantities. Once sold out they may or may not be available again.

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SKU: 70018085881

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William P Ross
Waukegan, 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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Adam
Whiting, 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.
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Reviewed in the United States on May 22, 2026
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Amazon Customer
Cuba, 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
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mackster
Carnegie, 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
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Stergios Papadimitriou
Grantham, 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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