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I would recommend, with caveats about the cost based on how much it would be used. Many government forms and other PDFs are already fillable, so PDFfiller isn't needed that often for the average person. However, it was very nice to use.
2015-12-29
Good so far; expensive, however, AND when I agreed to your discounted one year offer when I intended to cancel after one month, I didn't realize the sum offered was in addition to the $20 one month fee, so it didn't turn out to be such a great deal after all. I was canceling, because I honestly don't see myself using this much more if even ever again. However, for the discounted rate (WITHOUT the $20 added in), I thought 'why not?' I am going to evaluate over the next couple weeks to see if I really DO want to continue a subscription, discount or otherwise.
2016-04-15
Affordable, reliable, and flexible with changes. Could use a little more explaining to become more user friendly without having to get technical assistance all the time.
2017-08-14
all the features save so much time! and the price of using them at first seemed ridiculous, but once you realize how much time and effort this can save you the price automatically becomes such an amazing deal.
2019-06-25
Paul is a phenomenal customer support…
Paul is a phenomenal customer support rep. Very attentive, prompt and courteous. Took care of my issues immediately.Thank you Paul!
2019-05-19
etter than expected!
I us I nearly every day. It saves time and hassle,and it makes PDFS easy to customize. I love it!
I go this software to fill out forms, but it does SO much more than that! I can take educational PDFS, and change items to apply to my young students. Even the younger teachers in my group will send me a PDF, and ask me to "Do your magic" on it. My "magic" is PDF filler!
Wow....there isn't much I would change. It really works so very well. I might want to see a few more fonts available.
2020-03-05
The system was quite user-friendly, however the quality of the initial edited documents was poor, with a green tinge appearing behind the altered text. A note to Paul at customer service had a solution identified, which solved the problem.
2023-06-25
I wrote some legal documents using this…
I wrote some legal documents using this tool, it was much easier than other PDF editing tools I found. I was able to put my legal case together in an hour after wasting much more than that on other editing tools.
Excellent experience, terrific results.
2022-12-28
The product is great and very easy to…
The product is great and very easy to use. I had started a free trial for one time use, but forgot to cancel it and was charged for a full year, but when I contacted them they refunded my money straight away with no questions asked. I wish all companies were as good to deal with as this!
2021-03-04
PDF App - PCA Feature
The PDF App extends its capabilities with the innovative PCA feature designed to enhance your document management experience. This feature allows you to analyze and interact with your PDFs more effectively, making your workflow smoother and more efficient.
Key Features of the PCA Feature
Easy document analysis for quick insights
User-friendly interface that simplifies navigation
Customizable settings to suit individual preferences
Advanced search tools for specific content extraction
Integration with cloud services for seamless access
Potential Use Cases and Benefits
Students can summarize research papers quickly
Business professionals can extract key data from reports
Researchers can analyze large volumes of information effortlessly
Educators can prepare lesson materials with ease
Individuals can manage personal documents efficiently
This feature effectively tackles the common issue of information overload. By providing you with tools to analyze and manage your PDFs, the PCA feature allows you to focus on what matters most. You can efficiently locate essential information, saving you time and reducing frustration. Transform your PDF experience today.
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How do you do a PCA analysis?
Suggested clip
Statues: Principal Component Analysis (PCA), Step-by-Step YouTubeStart of suggested client of suggested clip
Statues: Principal Component Analysis (PCA), Step-by-Step
How do you perform a PCA?
Take the whole dataset consisting of d+1 dimensions and ignore the labels such that our new dataset becomes d dimensional.
Compute the mean for every dimension of the whole dataset.
Compute the covariance matrix of the whole dataset.
Compute eigenvectors and the corresponding eigenvalues.
How do you do a PCA?
Suggested clip
Statues: Principal Component Analysis (PCA), Step-by-Step YouTubeStart of suggested client of suggested clip
Statues: Principal Component Analysis (PCA), Step-by-Step
What is PCA and how does it work?
The main idea of principal component analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, while retaining the variation present in the dataset, up to the maximum extent.
When should I use PCA?
PCA should be used mainly for variables which are strongly correlated. If the relationship is weak between variables, PCA does not work well to reduce data. Refer to the correlation matrix to determine. In general, if most of the correlation coefficients are smaller than 0.3, PCA will not help.
What is PCA in simple terms?
Principal Components Analysis (PCA) is a technique that finds underlying variables (known as principal components) that best differentiate your data points. Principal components are dimensions along which your data points are most spread out: A principal component can be expressed by one or more existing variables.
Why do we do PCA?
PCA is a method used to reduce number of variables in your data by extracting important one from a large pool. It reduces the dimension of your data with the aim of retaining as much information as possible.
What is the purpose of PCA?
PCA is mostly used as a tool in exploratory data analysis and for making predictive models. PCA is the simplest of the true eigenvector-based multivariate analyses. Often, its operation can be thought of as revealing the internal structure of the data in a way that best explains the variance in the data.
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