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      "content": "<h2>File description</h2>\n\n<ul>\n<li><b>lc_trainingset.csv</b> - the training set (dataset you will use for training & evaluation)</li>\n<li><b>lc_testset.csv</b> - the test set (only used for generating predictions for the leaderboard ranking)</li>\n<li><b>sample_submission.csv</b> - a sample submission file in the correct format</li>\n</ul>\n\n<h2>Column descriptions</h2>\n\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th>Column Name</th>\n      <th>Description</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>loan_amnt</td>\n      <td>The listed amount of the loan applied for by the borrower. If at some point in time, the credit department reduces the loan amount, then it will be reflected in this value.</td>\n    </tr>\n    <tr>\n      <td>term</td>\n      <td>The number of payments on the loan. Values are in months and can be either 36 or 60.</td>\n    </tr>\n    <tr>\n      <td>int_rate</td>\n      <td>Interest Rate on the loan</td>\n    </tr>\n    <tr>\n      <td>installment</td>\n      <td>The monthly payment owed by the borrower if the loan originates.</td>\n    </tr>\n    <tr>\n      <td>grade</td>\n      <td>LC assigned loan grade</td>\n    </tr>\n    <tr>\n      <td>sub_grade</td>\n      <td>LC assigned loan subgrade</td>\n    </tr>\n    <tr>\n      <td>emp_title</td>\n      <td>The job title supplied by the Borrower when applying for the loan.*</td>\n    </tr>\n    <tr>\n      <td>emp_length</td>\n      <td>Employment length in years. Possible values are between 0 and 10 where 0 means less than one year and 10 means ten or more years.</td>\n    </tr>\n    <tr>\n      <td>home_ownership</td>\n      <td>The home ownership status provided by the borrower during registration or obtained from the credit report. Our values are: RENT, OWN, MORTGAGE, OTHER</td>\n    </tr>\n    <tr>\n      <td>annual_inc</td>\n      <td>The self-reported annual income provided by the borrower during registration.</td>\n    </tr>\n    <tr>\n      <td>verification_status</td>\n      <td>Indicates if income was verified by LC, not verified, or if the income source was verified</td>\n    </tr>\n    <tr>\n      <td>issue_d</td>\n      <td>The month which the loan was funded</td>\n    </tr>\n    <tr>\n      <td>loan_status</td>\n      <td>Current status of the loan</td>\n    </tr>\n    <tr>\n      <td>purpose</td>\n      <td>A category provided by the borrower for the loan request.</td>\n    </tr>\n    <tr>\n      <td>title</td>\n      <td>The loan title provided by the borrower</td>\n    </tr>\n    <tr>\n      <td>zip_code</td>\n      <td>The first 3 numbers of the zip code provided by the borrower in the loan application.</td>\n    </tr>\n    <tr>\n      <td>addr_state</td>\n      <td>The state provided by the borrower in the loan application</td>\n    </tr>\n    <tr>\n      <td>dti</td>\n      <td>A ratio calculated using the borrower’s total monthly debt payments on the total debt obligations, excluding mortgage and the requested LC loan, divided by the borrower’s self-reported monthly income.</td>\n    </tr>\n    <tr>\n      <td>earliest_cr_line</td>\n      <td>The month the borrower's earliest reported credit line was opened</td>\n    </tr>\n    <tr>\n      <td>open_acc</td>\n      <td>The number of open credit lines in the borrower's credit file.</td>\n    </tr>\n    <tr>\n      <td>pub_rec</td>\n      <td>Number of derogatory public records</td>\n    </tr>\n    <tr>\n      <td>revol_bal</td>\n      <td>Total credit revolving balance</td>\n    </tr>\n    <tr>\n      <td>revol_util</td>\n      <td>Revolving line utilization rate, or the amount of credit the borrower is using relative to all available revolving credit.</td>\n    </tr>\n    <tr>\n      <td>total_acc</td>\n      <td>The total number of credit lines currently in the borrower's credit file</td>\n    </tr>\n    <tr>\n      <td>initial_list_status</td>\n      <td>The initial listing status of the loan. Possible values are – W, F</td>\n    </tr>\n    <tr>\n      <td>application_type</td>\n      <td>Indicates whether the loan is an individual application or a joint application with two co-borrowers</td>\n    </tr>\n    <tr>\n      <td>mort_acc</td>\n      <td>Number of mortgage accounts.</td>\n    </tr>\n    <tr>\n      <td>pub_rec_bankruptcies</td>\n      <td>Number of public record bankruptcies</td>\n    </tr>\n  </tbody>\n</table>",
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      "content": "<img src=\"https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSctD44gMy0L_11BdiQhMYLE4Lr_SiIt9ALCVrX5mb61U0FSeFtgFIm9MQ6Pz62NebC2Q&usqp=CAU\" style=\"margin:0\">\n<br>\n<h2>Welcome, students of <a href='https://heicodersacademy.com/'>Heicoders Academy</a>'s AI200 course!</h2>\n<br>\n<p>For this competition, imagine that you work for the LendingClub company, which is headquartered in San Francisco, California. As the world's largest online loan marketplace, LendingClub specialises in facilitating personal loans, business loans, and financing of medical procedures.</p>\n\n<p>When LendingClub receives a loan application, the company has to make a decision for loan approval based on the applicant’s profile. Two types of risks are associated with the bank’s decision:</p>\n\n<ul>\n<li>If the applicant is likely to repay the loan, then not approving the loan results in a loss of business to the company</li>\n<li>If the applicant is not likely to repay the loan, i.e. he/she is likely to default, then approving the loan may lead to a financial loss for the company.</li>\n</ul>\n\n\n<p>Like most other lending companies, extending loans to ‘risky’ applicants is the largest source of financial loss. Each year, the financial industry loses billions of dollars due to loan defaults. This is why your Machine Learning team has been entrusted with the important task of mitigating this costly risk.</p><br>\n\n<p><b>The goal of this competition? Work with your team to build the optimal model that best predicts which loans are likely to be defaulted.</b> All the best, folks!</p><br>\n\n<p>Please note:</p>\n<ul>\n<li>You must compete in the same teams as previously registered at the start of the course.</li>\n<li>Individual submissions will be invalidated.</li>\n</ul>",
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      "name": "Evaluation",
      "content": "<p>Submissions are judged on <a href=\"http://en.wikipedia.org/wiki/Receiver_operating_characteristic\">area under the ROC curve</a>.</p>\n<hr>\n<h2>Submission File</h2>\n<p>Each line of your submission should contain an Id and a prediction of the probability that the loan application will be defaulted. Your submission file must have a header row. The file should have the following format:</p>\n<pre>Id,Predicted\n0,0.3\n1,0.8\n2,0.9\n...\n78236,0.1\n</pre>",
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      "name": "rules",
      "content": "<h2>Submission Limits</h2>\nEach team may submit a maximum of 6 entries per day.<br>\nYou may select up to 2 final submissions for judging.\n\n<h2>Competition Timeline</h2>\nStart Date: <b>18 Jun 2022 7:00 PM SGT</b><br>\nTeam Entry Deadline: <b>02 Jul 2022 09:00 PM SGT</b><br>\nEnd Date: <b>07 Jul 2022 09:00 PM SGT</b><br>\n\n<h2>Rules of the Competition</h2>\n\n<h3>Eligibility</h3>\nThe Competition is open to all AI200 students registered for the May 2022 Saturday cohort. Submissions must only be made by the same teams as previously registered via Google Forms. <b>All submissions by individuals will be invalidated.</b>\n\n<h3>Use of external data</h3>\nUnless otherwise expressly stated on the Competition Website, Participants must not use data other than what was provided in this competition to develop and test their models and Submissions. Heicoders reserves the right in its sole discretion to disqualify any Participant who is discovered to have undertaken or attempted to undertake the use of external data other than the Data in the course of the Competition.\n\n<h3>No sharing outside teams</h3>\nSharing code or data outside of teams is not permitted. If any code is made available to other teams, it must be done so publicly to all participating teams via the Competition Website discussion forums.\n\n<h3>One account per participant</h3>\nAs Kaggle strictly prohibits signing up from multiple accounts, no participant may submit from multiple accounts. If discovered by Kaggle, this may lead to permanent deactivation and suspension of affected Kaggle accounts.\n\n<h2>WINNING</h2>\n\n<h3>WINNERS' OBLIGATIONS</h3>\nAs a condition of receipt of the Prize, winning teams must:\n<ul>\n<li>deliver the final model’s software code to Heicoders Academy by <b>08 Jul 2022, 11:59PM</b> in the form of a Jupyter Notebook. </li>\nThe delivered software code must be capable of generating the winning Submission, and include a description of resources required to run the executable code successfully. This notebook is to be accompanied by associated documentation (consistent with the winning model documentation template available on the <a href=\"https://www.kaggle.com/WinningModelDocumentationGuidelines\">Kaggle wiki</a>) to be eligible for the Prize.\n<li>present their winning submission Notebook to the class on <b>09 Jul 2022 for a brief 5 minutes</b>. </li>\n</ul>\n\n<h3>DETERMINING WINNERS</h3>\nThis Competition is a challenge of skill and the final results are determined solely by leaderboard ranking on the <b>private leaderboard</b> at the end of the competition (subject to compliance with these Competition Rules). Participants' scores and ranks on the <b>public leaderboard</b> will be based on the evaluation metric described on the Competition Website, and determined by applying the predictions in the Submission to the ground truth of a validation dataset whose instances are a subset of the hidden test data used to generate the private leaderboard.<br><br>\n\nPrize awards are subject to verification of eligibility and compliance with these Competition Rules. All decisions of the Competition Sponsor and judges will be final and binding on all matters relating to this Competition. Competition Sponsor reserves the right to examine the Submission and any associated code or documentation for compliance with these Competition Rules. In the event that the Submission demonstrates a breach of these Competition Rules, Competition Sponsor may disqualify the Submission(s) at its discretion.<br>\n\n<h3>RESOLVING TIES</h3>\nA tie between two or more valid and identically ranked submissions will be resolved in favour of the tied submission submitted first.\n\n<h3>DECLINING PRIZES</h3>\nA Participant may decline to be nominated as a Winner by notifying Heicoders directly within 1 day following the Competition deadline, in which case the declining Participant forgoes any prize or other features associated with winning the Competition. Kaggle reserves the right to disqualify a Participant who so declines at Kaggle's sole discretion if Kaggle deems disqualification appropriate.",
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    {
      "name": "Timeline",
      "content": "* 2 July 2022 (Saturday) - You must make your first team submission by this deadline.\n* 7 July 2022 (Thursday) - Final Submission deadline.\n\nAll deadlines are at 9:00 PM SGT on the corresponding day unless otherwise noted. The organizers reserve the right to update the contest timeline if they deem it necessary.",
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