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Loan prediction system using ML models

Problem Statement We are having Housing Finance company and wants to automate the loan eligibility process based on customer detail provided while filling online application form. About the Data Set Loan_ID: Unique Loan ID Gender: Male/ Female Married: Applicant married (Y/N) Dependents: Number of dependents Education: Applicant Education (Graduate/ Under Graduate) Self_Employed: Self employed (Y/N) ApplicantIncome: Applicant income CoapplicantIncome: Coapplicant income LoanAmount: Loan amount in thousands Loan_Amount_Term: Term of loan in months Credit_History: Credit history meets guidelines Property_Area: Urban/ Semi Urban/ Rural Loan_Status: (Output Variable) Loan approved (Y/N) Import the required libraries Load and verify shape of the data Data Preprocessing 1.1 Analysis on Categorical Independent Variable vs Target Variable The proportion of married applicants is higher for approved loans. Distribution of applicants with 1 or 3+ dependents is similar a...
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Introduction to Deep Learning

Artificial intelligence is when machines can perform tasks that would normally require human intelligence. It includes machine learning, in which machines learn via experience and develop skills without the need for human intervention. Deep learning is a subset of machine learning. DL techniques are inspired by the human brain, learn from enormous volumes of data. The deep learning algorithm would repeat a task, modifying it slightly each time to enhance the outcome, like how we learn from experience. Because neural networks have various (deep) layers that permit learning, we refer to it as deep learning. Below are some of the applications of Deep Learning  • Self Driving Cars. • News Aggregation and Fraud News Detection. • Natural Language Processing. • Virtual Assistants. • Entertainment. • Visual Recognition. • Fraud Detection. • Healthcare. Deep learning concept was introduced by Geoffrey Hinton in the 1980s.  He did comparison of ML approaches to human brain. He created ...
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Data Types in Statistics

  Data Types in Statistics What is Data? We can say any piece of information is Data. Data is units of information in structured or unstructured format. Data available in different kind. Examples: Collection of relevant tweets, Records of yield in a farm over a period, Records of stock price every minute, Records of performance of a sports person. In general, there are four types of data. 1.Time Series Data 2. Cross sectional data 3. Pooled Data 4. Panel Data Time series data: Time series data is the set of observations on a variable at different timepoints. It is a collection of quantities that are assembled over even intervals in time and ordered chronologically. The data may be collected daily, weekly, monthly. Below image shows sample time series data Sample Time Series Data Cross-sectional data: Cross-sectional data are set of observations on two or more variables at the same time point. This data analysis is when you analyze a data set at a fixed point in time. The ...
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