Top 4% solution for the Kaggle M5 (Accuracy) competition. 6:30 Presentation and discussion begins ~7:45 Pick the next competition, then "breakout discussions" and BYOB This is an online event. Sliver Solution (Top 2%) for Kaggle M5 Forecasting competition / Kaggle M5沃尔玛销量时间序列预测竞赛 银牌方案(Top 2%) - songxxiao/m5_compete 社内でチーム組んでKaggleに参加してみた ~M5 Forecasting — Accuracy 参戦記~ 【38th solution】Kaggle M5 Forecasting -Accuracy~Team P 参戦記 コメントを投稿するには、 ログイン または 会員登録 をする必要があります。 The dataset The M5 dataset, generously made available by Walmart, involves the unit sales of various products sold We meet every two weeks to learn more about data science by discussing Kaggle competitions (https://www.kaggle.com). Participants are allowed to compete and be eligible for prizes in the first track, the second track, or both. Kaggle M5 competition: Walmart store forecasting. This m5 competition aims to forecast daily sales for the next 28 days i.e., till 22nd May 2016, and to make uncertainty estimates for these forecasts. Competition Link: M5 Forecasting Accuracy Kernel Link: To look at the complete code Final Notes This is my first competition and my first time working with Time Series Data. My next Silver medal came from M5 Accuracy Walmart Sales forecast Competition. The competition requires predicting store sales of individual items over a prediction period of 28 days. In this blog, I am just going to do forecasting and uncertainty will be performed in my next blog with the best-chosen model. competitions will be visible at the Kaggle platform, each one with its own separate leaderboard. additional details were all made av ailable on Kaggle, which hosted the competition, and the M5 competition’s website 5 . This is the 3rd most participated competition in Kaggle’s history and attracted more than 5500 teams. In 2020, I led a team of 3 to compete in a well-recognized Kaggle competition against 5600 teams After two months of hard-working, we won the Top 10% place in this competition. Modelling approach. To provide an overview of what the forecasting community can learn from Kaggle’s forecasting competitions, The code is quite short (<300 lines) and uses only fairly basic features in a LightGBM model. The dataset comes from historical sales of 10 stores from 3 US states. Please click the Attend Online button below to get the Zoom link. 2020 Kaggle M5 Walmart Unit Sales Prediction Competition. Mingling. the findings from the competitions migh t foreshadow the findings of the M5 competition. It appears Google researcher Da Huang was participating in Kaggle M5 forecasting competition on behalf of the team, but this was never disclosed to other M5 forecasting competition participants, neither other Kaggle team members were registered as part of “Google” team. 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