Most Viewed Models of the Month
Models Keywords (407)
Banking and Financial Services
6 models found.
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Term Deposits, also known as Specified Deposits, are an investment vehicle in which a lump-sum sum amount is placed for a... moreTerm Deposits, also known as Specified Deposits, are an investment vehicle in which a lump-sum sum amount is placed for a fixed length of time, ranging from one month to five years, at an agreed rate of interest.
Banks, non-banking financial companies (NBFCs), credit unions, post offices, and building societies are all places where you may get a term deposit.
The project aims to predict whether a customer will buy a term deposit plan or not.
The classic marketing bank dataset was originally uploaded in the UCI Machine Learning Repository. The dataset contains information on a financial institution's marketing campaign, which you must examine to discover methods to enhance future marketing efforts for the bank.
The "Accuracy_score" metric has been used to measure the model's performance. less
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Adult Census Income data have been extracted from the Census Bureau database, 1994 by Barry Becker and Ronny Kohavi.
The... moreAdult Census Income data have been extracted from the Census Bureau database, 1994 by Barry Becker and Ronny Kohavi.
The dataset provides 14 input variables that are a mixture of categorical, ordinal, and numerical data types.
The project's task is to determine whether a person makes over $50K a year or not.Dataset's link- https://archive-beta.ics.uci.edu/ml/datasets/adult.
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September 15, 2021 - MODEL_posted_by
Paturi Karthik,
579 views, 1 like
Bitcoin is the first decentralized digital currency. This means it is not governed by any central bank or some other... moreBitcoin is the first decentralized digital currency. This means it is not governed by any central bank or some other authority. Bitcoin’s market capitalization varies significantly from day to day but has hit a record high of more than $990.16bn. It remains the poster child for the cryptocurrency industry, though critics suggest that its volatility, slow speeds, energy usage, and higher transaction fees will put a limit on its growth. The objective of this project is to use different Deep Learning algorithms to predict the evolution of the Bitcoin price. We will compare the usual ARIMA time series with the LSTM and the GRU. less
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August 18, 2021 - MODEL_posted_by
Tarun Reddy,
913 views, 2 likes
Predicting the currency exchange rates is the regression problem in machine learning. There are changes in exchange rates... morePredicting the currency exchange rates is the regression problem in machine learning. There are changes in exchange rates every day that affect the income of a person, a business and can even affect the economy of a country. Thus, predicting the currency exchange rates can help an individual as well as a country in many ways.DATASET LINK: https://in.finance.yahoo.com/quote/INR%3DX?p=INR%3DX&.tsrc=fin-srchDATASET DESCRIPTION:1.date:- year and date2.open:- the opening value of the stock at that day3.high:- the highest value of the stock at that day4.low:- the lowest value of the stock at that day5.close:- closing of stock value6.volume and Adj CloseMODEL ACCURACY: 96 less
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Customers leaving the bank credit card services is the most common issue found by banks and in order to tackle this issue... more Customers leaving the bank credit card services is the most common issue found by banks and in order to tackle this issue they need to know which customer will get churned so in order to that they can take necessary actions to prevent that customer from being getting churned.
Here, we are given with a dataset where we have to predict whether the customer is going to leave the credit card service, if they are going to leave then we then we must predict them and show the bank manager about them and they would take some necessary actions to prevent them from leaving their bank.DataSet Link: https://www.kaggle.com/sakshigoyal7/credit-card-customers
The dataset consisted record of 10000 customers with 18 features.Class: Exisiting Customer, Attrited CustomerModel Gradient Boosting ClassifierAccuracy : 91 % F1-score : 72.06 %Note : If you are giving your own values then enter the value in Income_Category column as 30K or 24k don't input like 30000 , 29400 , etc. less
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March 27, 2021 - MODEL_posted_by
Tarun Reddy,
1,156 views, 3 likes
In this model, we will work with historical data about the stock prices of a publicly listed company. We will implement a... moreIn this model, we will work with historical data about the stock prices of a publicly listed company. We will implement a mix of machine learning algorithms to predict the future stock price of this company, starting with simple algorithms like averaging and then move on to advanced techniques like RNN and LSTM. The dataset which we used in this model contains columns like 1.date:- year and date, 2.open:- the opening value of the stock at that day, 3.high:- the highest value of the stock at that day, 4.low:- the lowest value of the stock at that day, 5.close:- closing of stock value, 6.volume and Adj Close. less
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