Archive Downloader

Updated : April 24th, 2022

Archive Downloader is tools to download archive.org books to pdf format ebooks, there is thousands free book on archive.org, some books can only be borrowed for 1 hour, these types of books do not have a download button as usual, Achive Downloader download these book in PDF format, Archive.org’s bookreader is supported, pdf page is image page, page has good resolution for read and print, new PDF file can print or read in Windows,Mac without limitation, share your ebook with friends.

Archive Downloader is tools to download 14 day loan book or 1 hour loan book in archive.org, it is simple easy to use, just 1-click,
There is demo limitation in demo version, only 10 pages download in demo, all pages in full version.

Step by Step Guide

Install Achive Downloader and run it, copy book link from browser and paste in downloader address bar, login arhive account,
Read book in downloader it, click Download button when it is ready,
it will download pages one by one, if user stop it , it resume downloading from begin of book.
it create pdf file in output folder when all pages downloaded.

Second Part: how to download the books from Archive in Digital Editions

you must understand that some book available at archive, you need to borrow it first, then you need to download the URLLINK.acsm that will be used by adobe digital edition, that’s why it is very important to be signed in, and there are 2 types of borrow: 1) borrow the book for 14 days and 2) Borrow the book for 1 hour

borrow the book for 14 days: What you need to do is go to the archive page of the book you want then click on borrow the book for 14 days, then press on download PDF/ePub… Then press on download the book, i highly recommend to download the book as pdf not epub cz the epub version is mostly corrupted and have missing parts… then a file called URLLINK.acsm get downloaded to your pc, mainly to your download folder, it is very small like few kb, you will need this file in the next steps

PS: IF SOMEONE ELSE BORROWED THE BOOK FOR 14 DAYS, YOU CANNOT BORROW IT UNLIT HE/SHE RETURNS IT, OR THE 14 DAYS PERIODE EXPIRE

2_ Borrow the book for 1 hour: these types of borrow does not have a download link on archive page like the 14 days borrowing period do, SO you cannot download URLLINK.acsm the usual way, but there is a work around it in order to be able to download the URLLINK.acsm file which will help us download the pdf book

So first make sure you click on borrow this book for 1 hour (very important step)

Next step, there is create book download link for the URLLINK.acsm file of the book you want to download

https://archive.org/services/loans/loan/?action=media_url&identifier=XXXXXXXXXXXXX&format=pdf&redirect=1

example for this:
Archive link: https://archive.org/details/pasta0000unse_m6m5
Identifier: pasta0000unse_m6m5
URLLINK.acsm download file link: https://archive.org/services/loans/loan/?action=media_url&identifier=pasta0000unse_m6m5&format=pdf&redirect=1

Now open the URLLINK.acsm link you got in your browser, anda file called URLLINK.acsm get downloaded to your pc, also mainly to your download folder, which you will need it in the next steps

You must have already clicked “Borrow for 1 hour” and have Adobe Digital Editions installed and set up
From the URL of the Archive book, copy the Identifier.
Example: For https://archive.org/details/legalfoundations0000comm,
the Identifier is “legalfoundations0000comm”
Paste the Identifier into this next link by replacing the “XXXXXXXXXXXXX”

https://archive.org/services/loans/loan/?action=media_url&identifier=legalfoundations0000comm&format=pdf&redirect=1

Now open the URLLINK.acsm link you got in your browser, anda file called URLLINK.acsm get downloaded to your pc, also mainly to your download folder, which you will need it in the next steps.

After the URLLINK.acsm is downloaded open it with adobe digital edition, and let it download the whole book you want as pdf file. the downloaded pdf file usually you can find it at C:/Users/your.pc.username/Documents/My Digital Edition as already stated the downloaded book is DRM protected so you need to remove the DRM protection. ePub DRM Removal will remove the DRM protection.

This is step by step guide to download Oreilly ebook

2). Find book to download, click “Reading” button to open book.

3). User open book in downloader, wait until “Download” button is ready, click download button to download ebook, it takes a while.

4). Downloader go through all book pages , it takes a while.

5). new PDF file created when finished, it saved in My document folder, “doc\ebook converter\safari online downloader\” .

About the Book

This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer.

Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks.

Who This Book Is For

If you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep-learning with Keras. A knowledge of Python is required for this book.

What You Will Learn

Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm

Fine-tune a neural network to improve the quality of results

Use deep learning for image and audio processing

Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases

Identify problems for which Recurrent Neural Network (RNN) solutions are suitable

Explore the process required to implement Autoencoders

Evolve a deep neural network using reinforcement learning

eBook DRM Removal