Looking for a collection of data science take home challenges datasets? Check out this list of open-source datasets that are perfect for practicing your data science skills.
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Data science take home challenges are a great way to get your feet wet in the data science industry. But sometimes, it can be hard to find good datasets to practice on. This collection contains a variety of datasets that are perfect for practicing your data science skills. From beginner to advanced, there is something here for everyone.
Data Science Take Home Challenges
A collection of data science take home challenges datasets from a variety of sources.
Data science take home challenges are a great way to get real-world practice with data science. But finding good datasets for these challenges can be a challenge in itself. This article contains a collection of links to datasets that can be used for data science take home challenges.
The datasets listed below are all free to use and free to download. Some of the datasets are from well-known sources, such as Kaggle and UCI Machine Learning Repository, while others are from less well-known sources. All of the datasets are suitable for use in data science take home challenges.
Datasets for data science take home challenges:
1. KaggleDatasets – This site contains a large collection of datasets that can be used for data science take home challenges. The datasets are categorized by topic, and there is a search function that makes it easy to find the dataset you need.
2. UCI Machine Learning Repository – This site contains a huge collection of machine learning datasets, including many that would be suitable for data science take home challenges. The site also includes descriptions of the datasets, which can be helpful in understanding what kind of challenge each dataset would be best suited for.
3. Amazon Open Data Registry – This site contains a large collection of Amazon-related datasets that can be used for data science take home challenges. The datasets are divided into categories, such as retail sales data and Amazon Web Services usage data, making it easy to find the dataset you need.
4. Yelp Dataset Challenge – This site contains a collection of Yelp-related datasets that can be used fordata science take home challenges. The challenge is to use the Yelp dataset to build models that predict restaurant rating stars from review text data. The prize for the challenge is $5,000, making it one of the more valuable prize pools for data science take home challenges.
This is a collection of data science take home challenges datasets. The goal is to provide a variety of different challenging datasets for people to practice their data science skills on. Each dataset has a description of what it is, what the data contains, and what the challenge is.
These datasets are a collection of data science take home challenges that I have encountered in my work as a data scientist. I hope that by sharing these datasets, other data scientists will be able to use them to practice their skills and improve their abilities.
The datasets range in size from a few hundred MB to several GB, and contain both structured and unstructured data. There is also a wide variety of formats, including CSV, JSON, XML, and SQL.
I have also included a brief description of each dataset, as well as some ideas for how to use the data. I hope you find these datasets useful!
Take home data science challenges are a great way to assess your skills as a data scientist. However, it can be hard to find quality datasets to use for these challenges. This article will provide you with a list of datasets that can be used for take home data science challenges.
The datasets listed in this article are all available on the UCI Machine Learning Repository. The UCI Machine Learning Repository is a great resource for machine learning datasets. All of the datasets listed in this article are free to download and use.
1. The Iris Dataset
2. The Titanic Dataset
3. The Adult Income Dataset
4. The Diabetes Dataset
5. The Breast Cancer Dataset
There is a collection of data science take home challenges datasets available on Github. The Dataset attends to the problem of classifying images of traffic lights by their color. The dataset contains images that are taken from different angles and different lighting conditions. The dataset also includes a CSV file that maps the image filenames to the correct classification label.
TheDataset is released under the MIT License.
This is a compilation of take home challenges that I have solved for various data science roles. The challenges are real and anonymized. I have put together this compilation to help other job seekers who are preparing for their data science interviews.
The datasets are in the form of csv files. Each dataset has a corresponding jupyter notebook where I have solved the challenge. The jupyter notebook contains the data wrangling, exploratory analysis, model building and evaluation.
I hope you find this helpful!
At the heart of data science is, well, data! Without data, there would be no science to carry out in the first place. In this article, we will be using a few datasets from previous take home challenges so that you can practice your data science skills on some real-world problems.
The first dataset comes from a take home challenge by Monzo, a UK-based challenger bank. The task was to predict whether or not a customer would stay with Monzo after 6 months. The dataset is fairly small, with only about 10,000 rows and 20 columns. However, it is a real-world dataset with many features that can be used to build a predictive model.
The second dataset comes from a take home challenge by Airbnb. The task was to predict the price of an Airbnb listing given a set of features about the listing. This dataset is much larger than the Monzo dataset, with over 300,000 rows and 50 columns. As such, it presents a more challenging problem for data scientists.
Both of these datasets are available for download below. We hope you enjoy practicing your data science skills on them!
AtInterview, we frequently get asked by our customers for examples of data science take home challenges that they can use to practice their skills. To help out, we’ve collected a list of datasets that are perfect for use in these types of exercises.
This list covers a wide range of topics, including machine learning, natural language processing,time series analysis, and more. And best of all, each dataset comes with a brief description and link to where you can find it.
So whether you’re looking for a dataset to practice your regression techniques or want to try your hand at building aRecommender System, this list has you covered.