{"id":13993193,"url":"https://github.com/the-black-knight-01/Data-Science-Competitions","last_synced_at":"2025-07-22T17:31:13.402Z","repository":{"id":41266784,"uuid":"200235232","full_name":"the-black-knight-01/Data-Science-Competitions","owner":"the-black-knight-01","description":"Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).","archived":false,"fork":false,"pushed_at":"2020-01-30T13:33:47.000Z","size":108,"stargazers_count":800,"open_issues_count":0,"forks_count":216,"subscribers_count":54,"default_branch":"master","last_synced_at":"2024-11-13T01:37:03.989Z","etag":null,"topics":["analytics-vidhya","competition-code","competitive-data-science-github","data-science","data-science-competition","data-science-competitions","datahack-competition","kaggle","kaggle-competition","kaggle-competition-for-beginners","kaggle-competition-solutions","kaggle-solutions-github","kaggle-winning-solutions-github","machine-learning","machinehack-competition","xgboost"],"latest_commit_sha":null,"homepage":"https://interviewbubble.com","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/the-black-knight-01.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-08-02T12:59:35.000Z","updated_at":"2024-10-28T16:56:40.000Z","dependencies_parsed_at":"2022-08-02T23:15:13.336Z","dependency_job_id":null,"html_url":"https://github.com/the-black-knight-01/Data-Science-Competitions","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/the-black-knight-01%2FData-Science-Competitions","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/the-black-knight-01%2FData-Science-Competitions/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/the-black-knight-01%2FData-Science-Competitions/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/the-black-knight-01%2FData-Science-Competitions/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/the-black-knight-01","download_url":"https://codeload.github.com/the-black-knight-01/Data-Science-Competitions/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":227143415,"owners_count":17737154,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["analytics-vidhya","competition-code","competitive-data-science-github","data-science","data-science-competition","data-science-competitions","datahack-competition","kaggle","kaggle-competition","kaggle-competition-for-beginners","kaggle-competition-solutions","kaggle-solutions-github","kaggle-winning-solutions-github","machine-learning","machinehack-competition","xgboost"],"created_at":"2024-08-09T14:02:15.981Z","updated_at":"2024-11-29T14:31:44.406Z","avatar_url":"https://github.com/the-black-knight-01.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"Please send pull request if you want to add more competition solutions.\n\nFor Comment and Suggestions: [Discusssion Thread:](https://gist.github.com/interviewBubble/b1654c18b20b944876e513d953d437fd#file-data-science-competitions-discussion)\n# 1. Kaggle\n\n## Regression\n\n#### Elo Merchant Category Recommendation\n\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82314#latest-525737))\n* 7th Place Solution  ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82055#latest-483943))\n* 10th Place Solution  ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82093#latest-529125))\n* 11th Place Solution  ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82127#latest-502682))\n* 19th Place Solution  ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82178#latest-480628))\n* 21th Place Solution  ([Explanation](https://www.kaggle.com/c/elo-merchant-category-recommendation/discussion/82235#latest-481035))([code](https://github.com/bestpredicts/ELO))\n\n\n## Classification \n\n#### Santander Customer Transaction Prediction\n\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/89003#latest-590312))\n* 2nd Place Solution  ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/88939#latest-534927))([code](https://github.com/KazukiOnodera/Santander-Customer-Transaction-Prediction))\n* 5th Place Solution  ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/88897#latest-517607))\n* 7th Place Solution ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/89023#latest-518634))\n* 9th Place Solution  ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/89302#latest-516440))\n* 10th Place Solution  ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/88997#latest-517584))\n* 29th Place Solution ([Explanation](https://www.kaggle.com/c/santander-customer-transaction-prediction/discussion/89034#latest-548982))([code](https://github.com/btrotta/kaggle-santander-2019))\n\n#### PetFinder.my Adoption Prediction\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/petfinder-adoption-prediction/discussion/102099#latest-589409))([code](https://www.kaggle.com/naka2ka/stack-480-speedup-groupkfold-with-no-dict))\n* 3rd Place Solution  ([Explanation \u0026 code](https://www.kaggle.com/wuyhbb/final-small))\n* 6th Place Solution  ([Explanation \u0026 code](https://www.kaggle.com/bminixhofer/6th-place-solution-code))\n* 8th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/adityaecdrid/8th-place-solution-code))\n* 10th Place Solution  ([Explanation \u0026 code](https://www.kaggle.com/chizhu2018/final-submit-two-10th-solution-private-0-442))\n* Place Solution  ([Explanation \u0026 code](https://www.kaggle.com/corochann/13-th-place-solution-ensemble-of-5-models))\n\n#### Santander Product Recommendation\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26835#latest-549998))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26824#latest-379386))([code](https://github.com/ttvand/Santander-Product-Recommendation))([Blog](https://ttvand.github.io/Second-place-in-the-Santander-product-Recommendation-Kaggle-competition/))\n* 3rd Place Solution - R language ([Explanation \u0026 code](https://www.kaggle.com/c/santander-product-recommendation/discussion/26899#latest-385293))\n* 4th Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26845#latest-549966))\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26841#latest-152148))([code](https://github.com/jturkewitz/SideProjects/tree/master/Kaggle/Santander_Prod))\n* 8th Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26838#latest-153042))([code](https://github.com/yaxinus/santander-product-recommendation-8th-place))\n* 11th Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26823#latest-180009))([code](https://github.com/rohanrao91/Kaggle_SantanderProductRecommendation))\n\n## Text Classification \n\n#### Jigsaw Unintended Bias in Toxicity Classification\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/discussion/100661#latest-590437))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/discussion/97471#latest-582610))\n* 4th Place Solution  ([Explanation](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/discussion/101927#latest-590658))([code](https://github.com/iezepov/combat-wombat-bias-in-toxicity))([Kaggle Kernel](https://www.kaggle.com/iezepov/wombat-inference-kernel))\n* 8th Place Solution  ([Explanation](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/discussion/100961#latest-586393))([code](https://www.kaggle.com/haqishen/jigsaw-predict))\n\n#### Quora Insincere Questions Classification\n\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/80568#latest-570793))\n* 2nd Place Solution  ([Explanation](https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/81137#latest-552221))\n* 3rd Place Solution  ([Explanation](https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/80495#latest-548808))([code](https://www.kaggle.com/wowfattie/3rd-place))\n* 4th Place Solution ([Explanation](https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/81632#latest-533550))([code](https://www.kaggle.com/kfujikawa/4th-place))\n* 7th Place Solution  ([Explanation](https://www.kaggle.com/c/quora-insincere-questions-classification/discussion/80561#latest-582439))\n\n#### Quora Question Pairs\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/quora-question-pairs/discussion/34355#latest-572705))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/quora-question-pairs/discussion/34310#latest-450693))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/quora-question-pairs/discussion/34288#latest-339489))\n* 7th Place Solution ([Explanation](https://www.kaggle.com/c/quora-question-pairs/discussion/34697#latest-349346))\n* Some interesting solutions from the web ([write-up](https://www.kaggle.com/c/quora-question-pairs/discussion/30260#latest-221245))\n* 24 Place Solution ([Explanation](https://www.kaggle.com/c/quora-question-pairs/discussion/34534#latest-420654))([code](https://github.com/aerdem4/kaggle-quora-dup))\n\n#### Toxic Comment Classification Challenge\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/52557#latest-533843))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/52612#latest-413355))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/52762#latest-434841))\n* 27 Place Solution ([Explanation](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/52719))([code](https://github.com/zake7749/DeepToxic))\n* Collection of winning solutions ([write-up](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge/discussion/72597#latest-437366))\n\n## Document Classification \u0026 Data extraction\n#### Tradeshift Text Classification\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/tradeshift-text-classification/discussion/10901#latest-62000))([code](https://github.com/daxiongshu/tradeshift-text-classification))\n* 28th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/c/tradeshift-text-classification/discussion/10629))\n* 71th Place Solution ([code](https://github.com/mandelbrot/kaggle-tradeshift-text-classification))\n* Another Solution ([code](https://github.com/jdlevitt/Tradeshift_kaggle))\n\n## Time series analysis \n\n#### Two Sigma: Using News to Predict Stock Movements\n* 49th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/silvernine/very-simple-nn-model-market-data-only))\n* 91th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/alluxia/lb-0-6326-tuned-xgboost-baseline))\n* 113th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/charleslandau/iterative-approach))\n* 119th Place Solution([Explanation \u0026 code](https://www.kaggle.com/yatzhash/news-features-without-headline-subjects))\n* Post-competition thoughts([write-up](https://www.kaggle.com/c/two-sigma-financial-news/discussion/102914#latest-593302))\n\n#### Web Traffic Time Series Forecasting\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43795))([code](https://github.com/Arturus/kaggle-web-traffic))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39395))([code](https://github.com/jfpuget/Kaggle/tree/master/WebTrafficPrediction))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39876))\n* 6th Place Solution ([Explanation](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39370))([code](https://github.com/sjvasquez/web-traffic-forecasting))\n* Tips from the winning solutions ([write-up](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/43535))\n* General Approach ([write-up](https://www.kaggle.com/c/web-traffic-time-series-forecasting/discussion/39367))\n\n#### Rossmann Store Sales\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/rossmann-store-sales/discussion/18024#latest-581685))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/rossmann-store-sales/discussion/17974#latest-477628))([code](https://github.com/entron/entity-embedding-rossmann))\n## QnA System:\n#### TensorFlow 2.0 Question Answering\n* [1st place solution](https://www.kaggle.com/c/tensorflow2-question-answering/discussion/127551)\n* [2nd place solution](https://www.kaggle.com/c/tensorflow2-question-answering/discussion/127333)\n* [3rd place solution](https://www.kaggle.com/c/tensorflow2-question-answering/discussion/127339)\n* [4th place Solution](https://www.kaggle.com/c/tensorflow2-question-answering/discussion/127371)\n\n## Recommendation System:\n#### Santander Product Recommendation\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26835#latest-549998\n))\n* 2nd Place Solution ([Explanation](https://ttvand.github.io/Second-place-in-the-Santander-product-Recommendation-Kaggle-competition/))([code](https://github.com/ttvand/Santander-Product-Recommendation))\n* 3rd Place Solution ([Explanation \u0026 code](https://www.kaggle.com/c/santander-product-recommendation/discussion/26899#latest-385293))\n* 4th Place Solution ([Explanation](https://www.kaggle.com/c/santander-product-recommendation/discussion/26845#latest-549966))\n\n## Coreference Resolution\n\n#### Gendered Pronoun Resolution\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/gendered-pronoun-resolution/discussion/90392#latest-521800))([code](https://github.com/sattree/gap))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/gendered-pronoun-resolution/discussion/90424#latest-522089))\n* Place Solution ([Explanation](https://www.kaggle.com/c/gendered-pronoun-resolution/discussion/90484#latest-522332))([code](https://github.com/zake7749/Fill-the-GAP))\n* Place Solution ([Explanation](https://www.kaggle.com/c/gendered-pronoun-resolution/discussion/90334#latest-521489))([code](https://github.com/boliu61/gendered-pronoun-resolution))\n* Top solutions ([write-up](https://www.kaggle.com/c/gendered-pronoun-resolution/discussion/90339))\n\n## Signal Processing\n#### LANL Earthquake Prediction\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94390))([code](https://www.kaggle.com/ilu000/1-private-lb-kernel-lanl-lgbm/))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94369))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94459))\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94484))\n* Gold Medal Solutions ([write-up](https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/94361))\n\n## Image Classification \n#### Cdiscount’s Image Classification Challenge\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45863))\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45733))([Video Tutorial with Eng subtitles](https://www.youtube.com/watch?v=Mw2vdYv4ups\u0026feature=youtu.be))\n* 7th Place Solution ([Explanation](https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45737#latest-327941))\n* 8th Place Solution ([Explanation](https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45850))\n* 9th Place Solution ([Explanation](https://www.kaggle.com/c/cdiscount-image-classification-challenge/discussion/45721#latest-327936))\n\n#### Right Whale Recognition\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/noaa-right-whale-recognition/discussion/18409#latest-170541))([code](https://www.dropbox.com/s/rohrc1btslxwxzr/deepsense-whales.zip?dl=1))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/noaa-right-whale-recognition/discussion/18325#latest-104535))([code](https://github.com/felixlaumon/kaggle-right-whale))\n\n## Video Challenge\n#### The 3rd YouTube-8M Video Understanding Challenge\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/youtube8m-2019/discussion/112296#latest-647992))\n* 6th Place Solution ([Explanation](https://www.kaggle.com/c/youtube8m-2019/discussion/112403#latest-649376))\n* 7th Place Solution ([Explanation](https://www.kaggle.com/c/youtube8m-2019/discussion/112349#latest-648466))\n\n## Semantic Segmentation \u0026 Instance Segmentation\n\n#### APTOS 2019 Blindness Detection\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/108065))\n* 2nd Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/107926))\n* 4th Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/107926#latest-624709))\n* 5th Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/107960))\n* 7h Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/107987))([code](https://github.com/BloodAxe/Kaggle-2019-Blindness-Detection))\n* 8th Place Solution ([Explanation](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/108030))([code](https://github.com/DrHB/APTOS-2019-GOLD-MEDAL-SOLUTION))\n* [🏅Gold Medal Solutions list 🏅](https://www.kaggle.com/c/aptos2019-blindness-detection/discussion/108307#latest-623987)\n\n#### iMaterialist (Fashion) 2019 at FGVC6:  \n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/discussion/95247#latest-567841))([code](https://github.com/amirassov/kaggle-imaterialist))\n* 2nd Place Solution([Explanation](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/discussion/95233#latest-551075))\n* 3rd Place Solution([Explanation](https://www.kaggle.com/c/imaterialist-fashion-2019-FGVC6/discussion/95234#latest-555537))\n\n#### TGS Salt Identification Challenge\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/69291#latest-523430))([code](https://github.com/ybabakhin/kaggle_salt_bes_phalanx))\n* 4th Place Solution  ([Explanation](https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/69178#latest-527751\n))([code](https://github.com/SeuTao/Kaggle_TGS2018_4th_solution))\n* 9th Place Solution  ([Explanation](https://www.kaggle.com/c/tgs-salt-identification-challenge/discussion/69053#latest-563912))([code](https://github.com/tugstugi/pytorch-saltnet))\n\n#### Airbus Ship Detection Challenge\n\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/airbus-ship-detection/discussion/74443#latest-456794))\n* 6th Place Solution  ([Explanation](https://www.kaggle.com/c/airbus-ship-detection/discussion/71782#latest-558831))\n* 8th Place Solution  ([Explanation](https://www.kaggle.com/c/airbus-ship-detection/discussion/71667#latest-558876))([code](https://github.com/SeuTao/Airbus-Ship-Detection-Challenge-2018_8th_place_solution))\n* 9th Place Solution  ([Explanation](https://www.kaggle.com/c/airbus-ship-detection/discussion/71595#latest-457550))\n* Few lessons learned (4th place) ([Explanation](https://www.kaggle.com/c/airbus-ship-detection/discussion/71667#latest-558876))\n\n\n#### 2018 Data Science Bowl (DSB2018)\n* 1st Place Solution ([Explanation](https://www.kaggle.com/c/data-science-bowl-2018/discussion/54741#latest-477226))([code](https://github.com/selimsef/dsb2018_topcoders/))\n* 2nd Place Solution ([Explanation \u0026 code](https://github.com/jacobkie/2018DSB))\n* 3rd Place Solution ([Explanation](https://www.kaggle.com/c/data-science-bowl-2018/discussion/56393#latest-540344))([code](https://github.com/Lopezurrutia/DSB_2018))\n* 4th Place Solution  ([Explanation](https://www.kaggle.com/c/data-science-bowl-2018/discussion/55118#latest-527734))([code](https://github.com/pdima/kaggle_2018_data_science_bowl_solution))\n\n\n## GAN\n#### Generative Dog Images\n* P1st lace Solution ([Explanation](https://www.kaggle.com/c/generative-dog-images/discussion/106324))\n* Place Solution ([Explanation](https://www.kaggle.com/c/generative-dog-images/discussion/104211))([code](https://www.kaggle.com/yukia18/sub-rals-ac-biggan-with-minibatchstddev))\n* Place Solution ([Explanation](https://www.kaggle.com/c/generative-dog-images/discussion/106514))([code](https://www.kaggle.com/lisali/sagan-submit-2?scriptVersionId=18714508))\n* Place Solution ([Explanation](https://www.kaggle.com/c/generative-dog-images/discussion/104281))([code](https://github.com/bestfitting/kaggle/tree/master/gandogs))\n* Place Solution ([Explanation](https://www.kaggle.com/c/generative-dog-images/discussion/104287))([code](https://www.kaggle.com/dvorobiev/doggies-biggan-sub-data-aug-3))\n* [Gold Medal Solutions](https://www.kaggle.com/c/generative-dog-images/discussion/106305)\n\n# 2. DataHack by Analytics Vidya\n\n#### Innoplexus Online Hiring Hackathon: Sentiment Analysis\n* 14th Place Solution ([code](https://github.com/pawangeek/Ccmps/tree/master/innoplexus))\n* 25th Place Solution ([code](https://github.com/rajat5ranjan/AV-Innoplexus-Online-Hiring-Hackathon-Sentiment-Analysis))\n* 27th Place Solution ([code](https://github.com/Laxminarayen/Innoplex_Hackathon))\n* 29th Place Solution ([code](https://github.com/chetanambi/Innoplexus-Online-Hiring-Hackathon-Sentiment-Analysis))\n\n#### Genpact Machine Learning Hackathon\n* 13th Place Solution ([code](https://github.com/rajat-1994/AV-Genpact-Hackathon))\n* 32th Place Solution ([code](https://datahack-prod.s3.amazonaws.com/submissions/genpact-machine-learning-hackathon/440_505172_cf_baseline.ipynb))\n\n#### Game of Deep Learning: Computer Vision Hackathon\n* 1st Place Solution ([code](https://github.com/narensahu13/AV-Game-of-Deep-Learning))\n* 2nd Place Solution ([code](https://github.com/salilmishra23/AnalyticsVidhya_GameOfDeepLearning))\n* 3rd Place Solution ([code](https://www.kaggle.com/tezdhar/avships-densenet-v3))\n* 5th Place Solution ([Explanation](https://docs.google.com/document/d/1ULIxyYW2b1zjoYolHI_rgneW8xkw3fVODw6fjqp9VXc/edit#heading=h.u1tdm64ah919))([code](https://github.com/xbassi/game_of_deep_learning))\n\n#### Capillary Machine Learning Hackathon\n* 4th Place Solution ([code](https://drive.google.com/file/d/1T2dGWdyCy7gCm5bPbKeZzpmBhKOdlLdx/view?usp=drive_open))\n* 12th Place Solution ([code](https://datahack-prod.s3.amazonaws.com/submissions/capillary-machine-learning-hackathon/443_624878_cf_code_eJkEZMW.py))\n* 13th Place Solution ([code](https://datahack-prod.s3.amazonaws.com/submissions/capillary-machine-learning-hackathon/443_622728_cf_current_best_y1yhRmZ.py))\n\n# 3. Machine Hack\n\n#### Predicting The Costs Of Used Cars - Hackathon By Imarticus Learning\n* 5th Place Solution ([code](https://github.com/chetanambi/Predicting-The-Costs-Of-Used-Cars-Hackathon-By-Imarticus-Learning))\n* 11th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/rajatranjan/fork-of-mh-predict-cost-of-used-cars-hackathon))\n\n#### Predict A Doctor's Consultation Fee Hackathon\n* 3rd Place Solution ([code](https://github.com/chetanambi/Predict-A-Doctors-Consultation-Fee-Hackathon))\n* 8th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/rajatranjan/predict-consultation-fee-doc-machinehack-re))\n\n#### Predict The Flight Ticket Price Hackathon\n* 3rd Place Solution  ([code](https://github.com/chetanambi/Predict-The-Flight-Ticket-Price-Hackathon))\n* 11th Place Solution ([Explanation \u0026 code](https://www.kaggle.com/rajatranjan/predict-flight-tickets-machine-hack1))\n\n#### Predicting Restaurant Food Cost Hackathon\n* 5th Place Solution ([code](https://www.kaggle.com/rajatranjan/machinehack-predict-food-prices))\n* 7th Place Solution ([code](https://github.com/chetanambi/Predicting-Restaurant-Food-Cost-Hackathon))\n\n# 4. Driven Data\n\n| Competition\n| ---\n| [America's Next Top (Statistical) Model](https://github.com/drivendataorg/americas-next-top-statistical-model)\n| [Box-Plots for Education](https://github.com/drivendataorg/box-plots-for-education)\n| [Countable Care: Modeling Women's Health Care Decisions](https://github.com/drivendataorg/countable-care)\n| [From Fog Nets to Neural Nets](https://github.com/drivendataorg/from-fog-nets-to-neural-nets)\n| [Keeping it Fresh: Predict Restaurant Inspections](https://github.com/drivendataorg/keeping-it-fresh)\n| [Naive Bees Classifier](https://github.com/drivendataorg/naive-bees-classifier)\n| [Senior Data Science: Safe Aging with SPHERE](https://github.com/drivendataorg/senior-data-science)\n| [Pri-matrix Factorization](https://github.com/drivendataorg/pri-matrix-factorization)\n| [Pover-T Tests: Predicting Poverty](https://github.com/drivendataorg/pover-t-tests)\n| [Random Walk of the Penguins](https://github.com/drivendataorg/random-walk-of-the-penguins)\n| [N+1 Fish, N+2 Fish](https://github.com/drivendataorg/n-plus-one-fish)\n| [Power Laws: Forecasting Energy Consumption](https://github.com/drivendataorg/power-laws-forecasting)\n| [Power Laws: Anomaly Detection](https://github.com/drivendataorg/power-laws-anomalies)\n| [Power Laws: Optimizing Demand-side Strategies](https://github.com/drivendataorg/power-laws-optimization)\n| [Power Laws: Cold Start Energy Forecasting](https://github.com/drivendataorg/power-laws-cold-start)\n| [Sustainable Industry: Rinse Over Run](https://github.com/drivendataorg/rinse-over-run)\n\n# 5. CrowdANALYTIX\n\n#### Extraction of product attribute values\n* 1st Place Solution ([Explanation](https://magicdata.eu/text-mining-machine-learning-detecting-skus/))\n\n#### PKPD Modeling: Predict Exacerbation in patients with COPD\n* 3rd Place Solution ([Explanation](https://mlwave.com/how-we-won-3rd-prize-in-crowdanalytix-copd-competition/))\n\n#### Identifying Superheroes from product images\n* 34th Place Solution ([code](https://github.com/skyprince999/Identify-Superheroes))\n* Another Solution: [code](https://github.com/kanashov/Identifying-Superheroes-from-Product-Images)\n* Another Solution: [code](https://github.com/lwkuant/Side_Project_Identifying_Superheroes)\n\n# 6. Hacker Earth\n#### Amazon ML Hiring Challenge\n* Score: 73.4% Solution ([Explanation \u0026 code](https://github.com/anu0012/Amazon-ML-Hiring-Challenge))\n* Score 66%: Solution ([Explanation \u0026 code](https://github.com/devNaresh/AmazonHiringChallange))\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthe-black-knight-01%2FData-Science-Competitions","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthe-black-knight-01%2FData-Science-Competitions","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthe-black-knight-01%2FData-Science-Competitions/lists"}