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  "source_url": "https://www.kaggle.com/competitions/codeasylums-asynamite-101/data",
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      "name": "data-description",
      "content": "<p>You have been given a job posting dataset. Your task is to classify the dataset into one of the industries (Ex - IT-Software / Software Services, Recruitment / Staffing, Real Estate / Property etc). However, You have given a training dataset. Using Machine Learning, find the pattern and predict industries on the given test dataset.</p>\n<h2>Data Description</h2>\n<h4><b>Id</b> : Unique Id</h4>\n<h4><b>company</b> : Company name which has listed the job post</h4>\n<h4><b>education</b> : Education required for given job post</h4>\n<h4><b>experience</b> : Experience required for given job post </h4>\n<h4><b>jobdescription</b> : Job Description for job post </h4>\n<h4><b>jobid</b> : Job Id for job post</h4>\n<h4><b>joblocation_address</b> : Job location for given job post</h4>\n<h4><b>jobtitle</b> : Title for given job post</h4>\n<h4><b>numberofpositions</b> : No of positions for given job post </h4>\n<h4><b>payrate</b> : Salary for given job post</h4>\n<h4><b>postdate</b> : Job Post Date</h4>\n<h4><b>skills</b> : Skills required for given job post</h4>\n<h4><b>industry</b> : Industry</h4>\n\n<h1> What am I predicting? </h1>\n<p>Predict industries based on your learned model</p>\n\n<h1>Files : </h1>\n<li> trainData.csv</li>\n<li> testData.csv</li>\n<li> sample_submission.csv</li>",
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      "name": "Description",
      "content": "**CodeAsylums Community**\n\nA Learning Ride, which imports you to the zone of Programming Affinity!\n\n**Learning** - lively, interactive, adaptive, collaborative with Mentorship & Sustainability \n\n**Ride** - An amusement ride full of fun, adventure & experience with care, which can help you to knockout your fears\n\n**Imports** - helps a file to become a part of existing package \n\n**Zone **- a player moves along various challenging paths with the team mindset \n\n**Programming** - CodeAsylums Community \n\n**Affinity** - Oops! We have a recursive error in the above line 🤖\n\n*Affinity to anything in long run becomes desire which can leads to greed and gambling!*\n\nAnd we are here for everything!\n\n**Let’s Play and Predict**\n\n\n**Asy~namite **\n\nLooking for a 201 GET **response** for a thanksgiving community **request**\n  \nChallenges for mixed mindsets including Analyser, Coders, Developers, Predictor, Debugger, Designer and Hacker. Come and join our community for brainstorming, problem solving, predictive analysis  and building competitive and interesting challenges.\n\nConnect at www.codeasylums.com\n\nCodeAsylums Community\ncommunity@codeasylums.com",
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      "name": "Evaluation",
      "content": "<p>The evaluation metric for this competition is <a href=\"https://www.kaggle.com/wiki/MeanFScore\"> Mean F1-Score</a>. The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision p and recall r. Precision is the ratio of true positives (tp) to all predicted positives (tp + fp). Recall is the ratio of true positives to all actual positives (tp + fn). The F1 score is given by:</p>\n<p>\\[ F1 = 2\\frac{p \\cdot r}{p+r}\\ \\ \\mathrm{where}\\ \\ p = \\frac{tp}{tp+fp},\\ \\ r = \\frac{tp}{tp+fn} \\]</p>\n<p>The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.</p>\n<h2>Submission Format</h2>\n<p>For each ID in the test set, you must predict Industry. The file should contain a header and have the following format:</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>Id,industry<br>1,Insurance<br>2,BPO / Call Centre / ITES<br>3,IT-Software / Software Services</pre>",
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    {
      "name": "rules",
      "content": "**No private sharing outside teams**\nPrivately sharing code or data outside of teams is not permitted. It's okay to share code if made available to all participants on the forums.\n\n**Individual Challenge**\nThis is an individual challenge not meant for teams\n\n**Submission Limits**\nYou may submit a maximum of 20 entries per day.\nYou may select up to 2 final submissions for judging.\n\n**Competition Timeline**\nStart Date: June 13, 2020 10:00 PM\nCompetition End Date: June 14, 2020 11:59 PM\n\n**Winner needs to also submit jupyter notebook. **",
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