The Cochrane Handbook for Systematic Reviews of Interventions is the official guide that describes in detail the process of preparing and maintaining Cochrane systematic reviews on the effects of healthcare interventions. All authors should consult the Handbook for guidance on the methods used in Cochrane systematic reviews. The Handbook includes guidance on the standard methods applicable to every review (planning a review, searching and selecting studies, data collection, risk of bias assessment, statistical analysis, GRADE and interpreting results), as well as more specialised topics (non-randomized studies, adverse effects, complex interventions, equity, economics, patient-reported outcomes, individual patient data, prospective meta-analysis, and qualitative research).
Academic or other non-commercial re-use of Handbook materialTo request permission to re-use material from the Handbook for academic and non-commercial purposes, please fill in this short webform. This will be sent to the Cochrane Support team who will notify Julian Higgins or James Thomas, the Handbook Senior Editors, as appropriate. If approved, these requests will be granted free of charge on condition that the source is acknowledged.
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You need to specify ID fields with certain API method calls. There are threetypes of IDs used within Google Books: Volume IDs - Unique strings given to each volume that Google Books knows about. An example of a volume ID is _LettPDhwR0C. You can use the API to get the volume ID by making a request that returns a Volume resource; you can find the volume ID in its id field.
Bookshelf IDs - Numeric values given to a bookshelf in a user's library. Google provides some pre-defined shelves for every user with the following IDs: Favorites: 0
Purchased: 1
To Read: 2
Reading Now: 3
Have Read: 4
Reviewed: 5
Recently Viewed: 6
My eBooks: 7
Books For You: 8 If we have no recommendations for the user, this shelf does not exist.
Custom shelves have IDs greater than 1000. A bookshelf ID is unique for a given user, i.e., two users can have a bookshelf with the same ID that refer to different bookshelves. You can use the API to get the bookshelf ID by making a request that returns a Bookshelf resource; you can find the bookshelf ID in its id field. User IDs - Unique numeric values assigned to each user. These values are not necessarily the same ID value used in other Google services. Currently, the only way retrieve the user ID is to extract it from the selfLink in a Bookshelf resource retrieved with an authenticated request. Users can also obtain their own user ID from the Books site. A user cannot obtain the user ID for another user via the API or the Books site; the other user would have to share that information explicitly, by email for example.
When viewing a particular bookshelf on the site, you can find the bookshelf ID in the as_coll URL parameter. Here is an example: =en&as_coll=0&num=10&uid=11122233344455566778&source=gbs_slider_cls_metadata_0_mylibrary
Google Books respects copyright, contract, and other legal restrictionsassociated with the end user's location. As a result, some users might not beable to access book content from certain countries. For example, certain booksare "previewable" only in the United States; we omit such preview links forusers in other countries. Therefore, the API results are restricted based onyour server or client application's IP address.
You use the download parameter to restrict the returned results to volumes that have an availabledownload format of epub by setting the to the valueepub.The following example searches for books with an epub download available:
The accessInfo section is of particular interest in determiningwhat features are available for an eBook. An epub is a flowing textformat ebook, the epub section will have anisAvailable property indicating if this type of ebook is available.It will have a download link if there is a sample for the book or if the usercan read the book either due to having purchased it or due to it being publicdomain in the user's location. A pdf for Google books indicates ascanned pages version of the ebook with similar details such as if it isavailable and a download link. Google recommends epub files foreReaders and SmartPhones, as scanned pages may be hard to read on these devices.If there is no accessInfo section, the volume is not available as aGoogle eBook.
I've found that most of the technical books published before about 1964 neverhad their copyrights renewed, so now are in the public domain. So I amendeavoring to digitize and post some selected books relating to the"vacuum tube age" of electronics here.
Many - maybe over half now - of these books werescanned by other people and contributed for me to post here. Many, manythanks to all the individuals who have helped out with this endeavor. Ifind that I do not have much time to scan books these days - the demands of the"day job" have increased much over the past few years - so I'm notdoing a lot of scanning myself. If you have material that you would liketo contribute, please send me an email.
After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression.The focus of the book is on model-agnostic methods for interpreting black box models such as feature importance and accumulated local effects, and explaining individual predictions with Shapley values and LIME.In addition, the book presents methods specific to deep neural networks.
All interpretation methods are explained in depth and discussed critically.How do they work under the hood?What are their strengths and weaknesses?How can their outputs be interpreted?This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.Reading the book is recommended for machine learning practitioners, data scientists, statisticians, and anyone else interested in making machine learning models interpretable. 2ff7e9595c
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