Participate in Data Science: Mock Online Coding Assessment - programming challenges in September, 2019 on HackerEarth, improve your programming skills, win prizes and get developer jobs. For me the I-COM Data Science Hackathon is one of rare occasions where data scientists get to experiment with data sources, interesting pieces of information. The final Prophet model was without any exogenous features, I made few adjustments (case counts for month-end and Sundays) as per cross-validation results since the model was not able to capture that even after introducing several features to help the model identify such patterns. Make sure you visit the DataHack platform for more such data science hackathons and practice problems! Here’s the prize money distribution for the top three winners: I love the problem statement posed by LTFS here. Here Data_Train.xlsx contains the data-set using which we need to train the model, Sample_submission as the name suggests specifies the format in which output needs to be submitted in the hackathon and Test_set is the data-set on which need we need to apply our model in order to predict flight ticket prices on the basis of which our score in the hackathon will be evaluated. These problem statements were taken from sector specialists and government officials. How has the representation of males and females evolved over time? Contribute to data-science-hackathon/Covid19Hackathon development by creating an account on GitHub. A Data Science Hackathon is an ultimate battleground for aspiring data scientists. Prepare a bucket of values using the derived temporal pattern, We fit a linear equation of each bucket using the, De-trend values in each bucket using the above-derived slope factor. Which league is the most suitable for particular type and age group of player? (and their Resources). ), Zone of state in which application was received (Central, East etc. Hackathon – IoT Hardware Problem statements: • “Develop an IoT enabled Android application to give real-time parking space available on the campus.” The application would ensure optimum use of resources, it would help save time and also be far more efficient than the traditional way of finding the parking slots on the streets. Before we go through their winning approaches, let’s congratulate the winners: You can check out the final rankings of all the participants on the contest leaderboard. Data Science FinHack 2 was a 9-day hackathon held between January 18th and 26th. What kind of sentiments get the most retweets. Accurately forecasting the number of cases received can help with resource and manpower management resulting in quick response on applications and more efficient processing. We computed representative values using the derived temporal patterns and multiple statistical measures. Derive statistical measures like mean+k(std), median+(l)MAD, Nth quantile) for a different set of k, l, N values. Following hyperparameters were used based on the time-split validation score: Detected all possible changes in training data using the “, Computed statistical measures like mean, median and standard deviation for regions between detected changes, Cluster the data using clustering techniques (used, Find the best temporal behavior (pattern) in each cluster, If different clusters in a dataset show different patterns, we consider that data has a complex pattern and segregate it on the basis of clusters, Cluster 1: Case count range (0-2724) – Best pattern: Day of Week, Cluster 2: Case count range (2772 – 4757) – Best pattern: Day of Week. Kickstarter is a funding platform where creators can share and gather interest in a particular creative project they’d like to launch. 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