To start easily, I suggest you start by looking at the datasets, Datasets | Kaggle. If you want to break into competitive data science, then this course is for you! Kaggle Solutions. 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. Experienced Data Analyst (Python & Qlik) & Database (SQL Server & MongoDB) Specialist - ppattnayak Let’s take a look at what’s happening at each of these steps. Many researchers have published peer-reviewed papers based on winning solutions at Kaggle … Kaggle Solutions and Ideas by Farid Rashidi. The score above is already pretty decent. This list will get updated as soon as a new competition finished. Sample script to download Kaggle files. Although Kaggle is not yet as popular as GitHub, it is an up and coming social educational platform. We have a new #1 on our leaderboard — a competitor who surprisingly joined the platform just two years ago. Graduate Student - Actively Seeking FT roles in Data Science & Analytics. With the model above we are already at the low end. He currently leads a company he founded that provides software solutions to banks. Posted on Aug 18, 2013 • lo [edit: last update at 2014/06/27. My apologies, have been very busy the past few months.] Everyone wants to better understand their customers. Whatever you need that is connected with Data Science or Machine Learning, you can probably find some clue about it on Kaggle. Download App. Kaggle.com is one of the most popular websites amongst Data Scientists and Machine Learning Engineers. Contribute to songxxiao/predict-future-sales development by creating an account on GitHub. Kaggle is the biggest Data Science community with over 2 million users. A 1kaggle.com similar approach was used to study the trends of people collaborating Github [2]. Insights platform Contentsquare analysed more than 1,400 websites 1. problems and post their solutions to the website. 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. We learn more from code, and from great code. 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. 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 … These solutions are publicly accessible and receive upvotes from other users on the platform. 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. The small range of scores compared to this base score is an indication of how hard this particular problem is. 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. Intro. As an analytics and management consultant, she was responsible for managing projects, identifying solutions, and developing support among senior-level … 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. In the premium mode of the extension, pulling from github repositories is enabled. GitHub Gist: instantly share code, notes, and snippets. 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. We collect these solutions and extract information from them that can inform us about the visualizations they use. It provides a whole Data Science ecosystem, ranging from competitions, kernels, discussions to blog and courses. You can create public and private datasets on Kaggle from your local machine, URLs, GitHub repositories, and Kaggle Notebook outputs. Kaggle Competition Past Solutions. This is a list of almost all available solutions and ideas shared by top performers in the past Kaggle competitions. This is a great place for Data Scientists looking for interesting datasets with some preprocessing already taken care of. Offered by National Research University Higher School of Economics. 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. 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. GitHub; Kaggle; LinkedIn; 10 min read Kaggle instacart (top2%) feature engineering and solution overview 2017/08/28. We scored in the 86th percentile, below one of the public collaboration solutions. Showing 1006 solutions within top 20 on each competition. This step assumes that you have Kaggle CLI installed and you’ve agreed to participate in the competition by visiting the competition page. At the time of writing, the scores in the Kaggle competition range from around 0.068 to around 0.064. The following steps are from the otto-kaggle-example.ipynb Jupyter notebook hosted on GitHub. Let us try to improve upon our score. This blog post aims at showing what kind of feature engineering can be achieved in order to improve machine learning models. There are two main kernels that were used, one for prediction , and one for Bayesian parameter optimization . Before you go any further, read the descriptions of the data set to understand wha… This post provides a description of the solution submitted for Kaggle competition (CORD-19) round #2 diagnostics task (link to github). 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. One second place solution for two 7th place solutions is a pretty good trade off! Date Competition Rank Upvote Title Github User Reply; 2020-10-06: stanford-covid-vaccine 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. I entered Kaggle’s instacart-market-basket-analysis challenge with goals such as : The Most Comprehensive List of Kaggle Solutions and Ideas. This page could be improved by adding more competitions and more solutions… In fact, such competitions have been held before in 2016, 2017, 2018 and 2019. Not necessarily always the 1st ranking solution, because we also learn what makes a … Kaggle Past Solutions Sortable and searchable compilation of solutions to past Kaggle competitions. If you are facing a data science problem, there is a good chance that you can find inspiration here! Predicting-Future-Sales-Kaggle. It was a very interesting problem, as the classes of data were very unbalanced, … Kaggle Competition Past Solutions. Shubin Dai, better known as Bestfitting on Kaggle or Bingo by his friends, is a data scientist and engineering manager living in Changsha, China. After reading, you can use this workflow to solve other real problems and use it as a template. The challenges on Kaggle are hosted by real companies looking to solve a … I was fortunate that Julian entered the competition. Hasbro Inc beat analysts' estimates for quarterly. Julia has over five years of experience delivering business insight through data analysis and visualization. Step 1: Download dataset. 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. I would recommend using the “search” feature to look up some of the standard data sets out there, such as the Iris Species, Pima Indians Diabetes, Adult Census Income, autompg, and Breast Cancer Wisconsindata sets. Research past solutions. Experience delivering business insight through Data analysis and visualization held before in 2016, 2017, 2018 and 2019 read. Otto-Kaggle-Example.Ipynb Jupyter notebook hosted on GitHub break into competitive Data Science problem, is. Around 0.068 to around 0.064 Scientists and Machine Learning Engineers scores compared to this base score an. For interesting datasets with some preprocessing already taken care of whatever you need that is connected with Data problem!, ranging from competitions, kernels, discussions to blog and courses low. 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