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And for the second time in the past year in a very short space of time, Google's lead developer of its new TensorFlow machine learning framework, Simon Rabinovitz, presented a number of machine learning related talks. Rabinovitz started his talk at the conference with some basic information on TensorFlow and then discussed different types of training tasks, and showed a good example of each. There are several types of classification problem that can potentially be solved by a TensorFlow GPU task, including: (1) Classification of images into distinct classes, such as dogs, cows, etc. ; (2) Classification of objects into a subset of specific classes, such as cars, trucks, etc. ; (3) Classification of objects into a subset of all classes, such as apples, horses, etc. Each user only needs to learn one feature, and their neural network models can be trained easily and efficiently on anything from this single class.. ‘Compress PDFs ›‹ Compressing PDF to reduce the amount of traffic on your website is one of the simplest and most common tasks that most websites face as the number of visitors grows. If your website is not optimized to compress the most needed part of the document like images, CSS, and JavaScript, your website will look unprofessional and users might forget to download your content. ‘Exclude parts of images ›‹ In case you want to optimize a section of the documents (with a specific image, for instance), you can use the file explorer interface provided by Google Chrome to view the file in full screen mode. ‘Easily organize your documents ›‹ Once you open or print a document, it usually starts with the title and description, which are very important. Also, you can have a series of folders per subject and sub-subject to organize more easily the information that is not essential for your studies.. Print your documents and fax them without having to wait for the printer.