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The website use state of the art Neural Networks to classify your Fraud_Detection of Cards. You are welcome to use this site to predict how much stars your fraud . Using this website is pretty straight forward. In this Fraud_Detection the data is comes from the csv data set and we can find the accuracy

Technical Details

The system follows the steps given below to classify reviews and get the probability of review to belong to any Fraud_Detection. When the Card data is entered and submit is clicked, the following steps occur at the server

Tokenization

Tokenization is the task of chopping it up into pieces, called tokens ,Data Visualization for checking the distribution for Genuine cases & Fraud cases for each feature, such as punctuation. The system uses spacy, a free, open-source library for tokenization of the input review.

Once the review is converted to tokens, the tokens are mapped on integer indexes according to the vocabulary in use by the system. At this point the system is ready to feed the review into the model.

Running model

The model is then fed the indexed review.

Display Result

At last, the system displays the results it has infered from gthe model in the form oa a simple bar chart.

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Inventory management is the supervision of non-capitalized assets (inventory) and stock items. A component of supply chain management, inventory management supervises the flow of goods from manufacturers to warehouses and from these facilities to point of sale.

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Recommendation System for movies Recommendation systems are becoming increasingly important in today’s extremely busy world. People are always short on time with the myriad tasks they need to accomplish in the limited 24 hours. Therefore, the recommendation systems are important as they help them make the right choices, without having to expend their cognitive resources.

The purpose of a recommendation system basically is to search for content that would be interesting to an individual. Moreover, it involves a number of factors to create personalised lists of useful and interesting content specific to each user/individual. Recommendation systems are Artificial Intelligence based algorithms that skim through all possible options and create a customized list of items that are interesting and relevant to an individual. These results are based on their profile, search/browsing history, what other people with similar traits/demographics are watching, and how likely are you to watch those movies. This is achieved through predictive modeling and heuristics with the data available.