In this webinar we’ll dive into each of the Lookup functions – powerful additions to your analyst’s toolkit. Creating my own dataset helped me gain more appreciation for web curated datasets and web scraping html-parser tools in Python. I've managed to find the KDD'99 dataset, the Credit Card Fraud dataset on kaggle, and the dataset for Data Mining Contest 2009. You can share your analyses with colleagues—without the dreaded “but it works on my machine” scenario. They have more than 350 datasets in total – with more than 200 as Featured datasets. He helps conversion-driven digital businesses make informed marketing decisions.He previously worked at Google as a digital marketing consultant for travel clients in EMEA. Please check out that project if you are interested in building an Image Recognition model with one of these datasets.Connor Shorten is a Computer Science student at Florida Atlantic University. You’re trying to figure out what each row and column represent, and no one seems to have precise documentation.What if we could ensure our datasets were clearly documented? This goes beyond just having a data dictionary for feature definitions.What if we knew who collected the data, the sources and methodology they used, and if any data is missing? Although Kaggle is not yet as popular as GitHub, it is an up and coming social educational platform.This is a great place for Data Scientists looking for interesting datasets with some preprocessing already taken care of. Most importantly, there’s a large variety of datasets related to marketing, ecommerce, and sales.When starting to analyze your marketing data, finding relevant datasets to combine with your original one is useful. A good example of this is the Google Analytics dataset from the previous section. This can be a source of inspiration but also a time saver, especially in the initial stage of an analysis.
This is my data mining project for CS573 (dataset is from Kaggle: https://www.kaggle.com/yelp-dataset/yelp-dataset) - jinggong1995/Text-Mining In the analysis I look at various visualizations and also compare tree-based machine learning algorithms on predicting student grades. They're… Alex is an independent consultant in marketing analytics and data science. An obvious option is your local desktop or laptop. Unlike other features in Kaggle, its use may result in costs for computation.Kaggle doesn’t cover all aspects of a data and analytics workflow. Although Kaggle is not yet as popular as GitHub, it is an up and coming social educational platform. Kaggle.com is one of the most popular websites amongst Data Scientists and Machine Learning Engineers. Also a fun dataset to play around with Generative Adversarial Networks generating unique fruit designs.Gender Recognition by Voice — csv w/ audio frequency statisticsI would like to see this dataset as raw audio files, however, it is still possible to build a neural network classifiers that will be able to separate voice data into male and female. You’re gazing over a large data file with lots of numbers but little explanation. Alternatively, you can go the Kaggle way by working with Kaggle Notebooks (previously known as Kaggle Kernels). On Kaggle I found this dataset on student grades. And there’s an added bonus: Given an initial dataset, Kaggle can make recommendations for relevant, complementary datasets. It lowers the barrier to entry and empowers marketers to get directly involved in the development of AI and machine learning for projects. KDD Cup center, with all data, tasks, and results.
Research interests in data science, deep learning, and software engineering. I wouldn’t be surprised to see more integrations since Kaggle is now part of Google Cloud.As a concept, AutoML isn’t entirely new, but making it accessible as a product en masse via Kaggle is a noteworthy development.
A little preprocessing will need to be done to funnel this dataset into a character-level recurrent neural network.
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