Loan Eligibility Prediction Tutorial | Python Projects For Data Science | Python Training | Edureka
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This Edureka video on "Loan Eligibility Prediction Tutorial” will provide you with comprehensive and detailed knowledge of Data Science concepts with a hands-on project where you will learn to develop a Loan Eligibility Prediction model using Python. In the process you will learn popular Machine Learning Algorithms and explore numerous Python Libraries. Following pointers will be covered in this Loan Eligibility Tutorial video:
00:00:00 Introduction
00:01:00 What is Loan Eligibility Prediction?
00:01:52 What is Data Science?
00:02:15 What is Machine Learning?
00:02:46 Types of Machine Learning Algorithms
00:03:44 Supervised Learning Algorithms
00:04:57 Algorithms For Loan Eligibility Prediction Project
00:05:02 Decision Tree Algorithm
00:07:23 Naive Bayes Theorem & Naive Bayes Classification
00:08:52 Why Python?
00:09:38 Python Libraries (NumPy, Pandas, Scikit learn, Matplotlib)
00:11:08 Project Implementation
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#edureka #edurekadatascience #datascienceproject #loanelibilityprediction #pythonprojects #datasciencetutorial #datasciencetraining #pythontutorial #pythonlibraries #decisiontreealgorithm #naivebayestheorem
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About the Master's Program
This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands-on expertise. By the end of the program, you will be ready for seasoned Data Science job roles.
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There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Scientist, Masters Program is designed and developed to accommodate various professional backgrounds.
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The recommended duration to complete this program is 34 weeks, however, it is up to the individual to complete this program as per their own pace
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