In the premium mode of the extension, pulling from github repositories is enabled. He currently leads a company he founded that provides software solutions to banks. Julia has over five years of experience delivering business insight through data analysis and visualization. Kaggle Solutions. Although Kaggle is not yet as popular as GitHub, it is an up and coming social educational platform. Intro. Posted on Aug 18, 2013 • lo [edit: last update at 2014/06/27. We collect these solutions and extract information from them that can inform us about the visualizations they use. These type of predictive modeling contests are compelling as a pedagogical exercise as they allow students to engage with real data and provide automatic feedback on performance in both an absolute (e.g. I was fortunate that Julian entered the competition. Kaggle Past Solutions Sortable and searchable compilation of solutions to past Kaggle competitions. Whatever you need that is connected with Data Science or Machine Learning, you can probably find some clue about it on Kaggle. The Most Comprehensive List of Kaggle Solutions and Ideas. This is a list of almost all available solutions and ideas shared by top performers in the past Kaggle competitions. I entered Kaggle’s instacart-market-basket-analysis challenge with goals such as : Hasbro Inc beat analysts' estimates for quarterly. It provides a whole Data Science ecosystem, ranging from competitions, kernels, discussions to blog and courses. GitHub; Kaggle; LinkedIn; 10 min read Kaggle instacart (top2%) feature engineering and solution overview 2017/08/28. One second place solution for two 7th place solutions is a pretty good trade off! Download App. You can create public and private datasets on Kaggle from your local machine, URLs, GitHub repositories, and Kaggle Notebook outputs. Let’s take a look at what’s happening at each of these steps. The kind of tricky thing here is that there is not really any way of gathering (from the page itself) which datasets are good to start with. This page could be improved by adding more competitions and more solutions… Kaggle is the biggest Data Science community with over 2 million users. Kaggle has received global recognition ever since it was founded for its high standard competitions which have proven to be real-world solutions and used by many companies like Microsoft, CERN, Merck, Adzuna. GitHub Gist: instantly share code, notes, and snippets. Walmart Kaggle Competition How I Achieved a Top 25% Score in the Walmart Classification Challenge View on GitHub Download .zip Download .tar.gz The Walmart Data Science Competition. Date Competition Rank Upvote Title Github User Reply; 2020-10-06: stanford-covid-vaccine A 1kaggle.com similar approach was used to study the trends of people collaborating Github [2]. As an analytics and management consultant, she was responsible for managing projects, identifying solutions, and developing support among senior-level … This step assumes that you have Kaggle CLI installed and you’ve agreed to participate in the competition by visiting the competition page. Sample script to download Kaggle files. If you want to break into competitive data science, then this course is for you! Research past solutions. We have a new #1 on our leaderboard — a competitor who surprisingly joined the platform just two years ago. Kaggle is a popular platform that enables companies and researchers to host predictive modeling competitions open to analysts, statisticians, and data scientists all over the world. Predicting-Future-Sales-Kaggle. With the model above we are already at the low end. Many researchers have published peer-reviewed papers based on winning solutions at Kaggle … Kaggle Solutions and Ideas by Farid Rashidi. There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. These solutions are publicly accessible and receive upvotes from other users on the platform. After reading, you can use this workflow to solve other real problems and use it as a template. We scored in the 86th percentile, below one of the public collaboration solutions. It was a very interesting problem, as the classes of data were very unbalanced, … Everyone wants to better understand their customers. This blog post aims at showing what kind of feature engineering can be achieved in order to improve machine learning models. Shubin Dai, better known as Bestfitting on Kaggle or Bingo by his friends, is a data scientist and engineering manager living in Changsha, China. If you are facing a data science problem, there is a good chance that you can find inspiration here! Contribute to songxxiao/predict-future-sales development by creating an account on GitHub. The extension can publish to public and private repositories and can as well update the content of a kaggle kernel/script from an existing ipynb file or a script (R or python) from your repository. Kaggle.com is one of the most popular websites amongst Data Scientists and Machine Learning Engineers. My apologies, have been very busy the past few months.] We learn more from code, and from great code. The small range of scores compared to this base score is an indication of how hard this particular problem is. In fact, such competitions have been held before in 2016, 2017, 2018 and 2019. This post provides a description of the solution submitted for Kaggle competition (CORD-19) round #2 diagnostics task (link to github). At the time of writing, the scores in the Kaggle competition range from around 0.068 to around 0.064. Kaggle Competition Past Solutions. Let us try to improve upon our score. Kaggle Competition Past Solutions. I was quick to find out in the early days that this wasn’t the first time SIIM (Society for Imaging Informatics in Medicine) was hosting such a competition. problems and post their solutions to the website. Experienced Data Analyst (Python & Qlik) & Database (SQL Server & MongoDB) Specialist - ppattnayak The following steps are from the otto-kaggle-example.ipynb Jupyter notebook hosted on GitHub. This list will get updated as soon as a new competition finished. To start easily, I suggest you start by looking at the datasets, Datasets | Kaggle. Graduate Student - Actively Seeking FT roles in Data Science & Analytics. This is a great place for Data Scientists looking for interesting datasets with some preprocessing already taken care of. The score above is already pretty decent. The solution is implemented in 3 phases (Figure 2) of data pre-processing of two datasets: diagnostics task and Kaggle , calculating word embeddings and Word2Vec sentence similarity between task sentences and article body sentences, and selects the top rank … Not necessarily always the 1st ranking solution, because we also learn what makes a … Insights platform Contentsquare analysed more than 1,400 websites 1. In this Kaggle competition, Rossmann, the second largest chain of German drug stores, challenged competitors to predict 6 weeks of daily sales for 1,115 stores located across Germany.According to the information provided, sales are influenced by many factors, including promotions, competition, school and state holidays, seasonality, and locality. Before you go any further, read the descriptions of the data set to understand wha… Vassar Labs is an IoT, Machine Learning and AI based based solutions provider in last mile visibility and decision support started by successful technology entrepreneurs. Normally in a Kaggle competition, it is easy to see who has a good solution and who doesn’t - and obviously you can ask others with good solutions to team up. The challenges on Kaggle are hosted by real companies looking to solve a … There are two main kernels that were used, one for prediction , and one for Bayesian parameter optimization . Step 1: Download dataset. After the competitions, it is common for the winners to share their winning solutions” (as written in the article, “Learning From the Best”) Reason #3 — Real data to solve a Real problem => Real motivation. 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