Tools which we provide
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Lets you get basic insights from your own data. Just upload your file and get the analysis in just one click.
On basic level, the classification model made from the data uploaded makes it easier for the user to locate and retrieve it.
It is a tool which helps you find and rectify misspelled words in your text in just one click.
It allows us to predict a continuous outcome variable (y) based on the value of one or multiple predictor variables (x).
Details of the Tools mentioned
Commonly known as the "Autocorrect" feature, the paragraph spellchecker is a very popular feature in social media and other
platforms. By using A.I. algorithm, this tool identifies the mispelled words in a paragraph which you have typed.
Whenever the mispelled words are identified, they are highlighted and appropriate contextual suggestions are made so as to rectify them. The suggestions are made by prioritizing the most common words used in normal conversations.
This feature ultimately helps the users recognize their spelling mistakes in their text, and get rid of them before using that text elsewhere.
As its name says, data analysis comprises of finding hidden patterns and stats in the data by analyzing it. Our website makes this analysis possible for you in just one click, without requiring any programming from you.
We take data from you in .csv format. The uploaded data is then processed with certain data analysis tools and methods to draw insights from it. We use analytical and logical reasoning to gain information from the data.
The information like description of the data, types of columns, min/max and unique values of each column etc. is fetched from the analysis in a well and tabulated form.
The main purpose of data analysis is to find meaning in data so that the derived result can be used to make informed decisions.
Regression is a machine learning technique which is used to predict output values based on some
input features from the data fed. For example, relationship between rash driving and number of road accidents
by a driver can be studied through regression.
We implement regression on our website by letting the you upload your .csv dataset and forming a predictive model from it which investigates the relationship between a dependent (target) and independent variable(s) (predictor).
To remove bias from the data, we use the concept of splitting the data into training and testing subsets. Further more, the users can even predict values from their own set of inputs using the trained regression model. The regression algorithms provided by us are: Linear, Bayesian, Ridge, Lasso and Nearest Neighbor regression.
Classification of data is another machine learning technique which is used to segregate the data into some labelled
classes. For example, grouping the height data into classes like "Tall", "Medium" and "Short".
To implement classification on our website, we take data from you in .csv format. The uploaded data is then acted upon with the classification machine learning algorithm to generate a model that finds relations between the dependent (target) and independent variable(s) (predictor).
After training the model based on the selected parameters, the accuracy of the test set is displayed. Further more, the users can even predict classes from their own set of inputs using the trained classification model. The type of classification algortihms provided are: K-Nearest Neighbors, Support Vector Machines, Decision Tree, Logistic Regression, Naive Bayes and Random Forest.
"Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a Freeway."Elliot Alderson