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* * * * * Photoshop Elements, which is free, offers many similar capabilities to Photoshop in order to enable amateur photographers to get their hands dirty. However, Photoshop Elements does not support much of the advanced editing of Photoshop, so it’s quite a different experience. • Create and edit images * * * * • Convert images * * * * • Promote websites * * *
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Both Photoshop and Elements have evolved a lot over the years. Here we’re going to walk you through the difference between the two. The Power of Photoshop Photoshop has become the standard for designers and graphic artists. It is used for every part of the design process from creating high-resolution graphics to editing photos. Photoshop has a lot of plugins and other tools that are essential to creating professional looking graphics. Photoshop is quite powerful, allowing designers and photographers to do things that would be difficult with other programs. You can crop, resize, and rotate any image in Photoshop. It has specialised tools such as selective colour, and vector editing tools. The Elements Elements is a graphics editor for photographers. It is an alternative to the expensive CS6 version of Adobe Photoshop. It’s simple, intuitive and easy to use. Elements is a lot like Photoshop CS4 and it is still very good. However, the latest version, CS6, is clearly a much better platform for designing and editing images. The latest version of Elements is Photoshop CC. There are some great features in CS6 that will not be found in Elements or the upcoming Photoshop Creative Cloud. The Difference Between Elements and Photoshop The small team at Adobe came up with the idea of providing a simple, user friendly and powerful tool for photographers and designers. This would be the ultimate tool for anyone who just likes to create pictures. The latest version of Elements has a lot more tools than Photoshop. However, Photoshop still has some amazing features, such as the tools for cropping images, or creating images from scratch. In both programs you’ll find a library of specialized tools for images, including filters and effects. Adobe Elements Adobe Elements is a graphics editor for photographers, web designers and hobbyists. It’s very easy to use and has lots of functions that most people don’t realize are there. It’s is the answer to “why is Photoshop so complicated?” It’s very powerful, but also very simple. You can do things in Elements that you’d never be able to do in Photoshop. Adobe made a conscious decision when they first developed Elements to keep it simple and intuitive. They think that this is the best way to create graphics and images for the world we live in today. Adobe was influenced by Mac OS and the simplicity of the interface. I think 388ed7b0c7
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Q: Normalized weights of Dataset I was reading an explanation given on how to create a normalised weight for a dataset. In short the author says that, if the dataset can be represented as a vector then the weights will be inversely proportional to the length of the vector. The author has mentioned an example with hot questions. The vector length is proportional to the number of votes. I was a bit stumped. How does one derive a vector from a set of points? A: Just as the author said, the lengths of vectors are proportional to their values. If your data is $x_1, \dots, x_N$ which have length $N$, then the vector with the same coefficients but normalized to sum to one is $\frac{x_1}{N},\dots,\frac{x_N}{N}$. (For convenience this can be arranged so that it has $N$ entries, but it doesn’t really matter. You can also normalize to have length one, which is just multiplying by the constant factor $\frac{1}{\sqrt{N}}$ in the denominator). In a dataset, if there’s a vector $x_1,\dots,x_N$ which has length $N$ and represents the values for each data point, then what you are looking for is a vector $w_1,\dots,w_N$ (we can treat vectors as matrices for convenience) which represents the weights that you should use to multiply your data points. The point here is that the vector $w_1,\dots,w_N$ should have length $N$ just as the vector $x_1,\dots,x_N$. A very simple example is given by the list $1, 2, 3, 4, 5$ of lengths which are already normalized. What you’re looking for is vectors $w_1,w_2,w_3,w_4,w_5$ which add up to $1$ but which represent the coefficients of the five weights. If you don’t have weights to give to the data points, then this will be harder. Sometimes you have an explicit list of weights or importance (for example, so you can give different weights to questions which are hard vs. easy, or you might want to give higher weights to famous questions, or you
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