This repository contains solutions to interview problems from the DataLemur website. DataLemur is a platform that offers a variety of interview questions covering topics such as SQL, statistics, Python, probability, and machine learning. The goal of this repository is to provide clear and well-documented solutions to help individuals prepare for interviews in these domains.
DataLemur is a valuable resource for individuals looking to enhance their skills in various aspects of data science and analytics. This repository aims to offer solutions to the interview problems available on the DataLemur website. Whether you are a job seeker preparing for interviews or a curious learner looking to deepen your understanding of these topics, you'll find this repository helpful.
The problems on DataLemur cover a wide range of topics. Here are the main categories:
- SQL
- Statistics
- Python
- Probability
- Machine Learning
Each category contains a set of problems designed to assess your proficiency in that specific area.
To get started with this repository, follow these steps:
- Clone the repository to your local machine:
git clone https://github.com/jhonatangopereira/DataLemur-DataScience-Interview-Challenges.git
- Navigate to the specific category or problem you are interested in.
- Review the problem statement and explore the provided solution.
- If you have a better or more optimized solution, feel free to contribute! See Contribution Guidelines for details.
The repository is organized into folders based on problem categories. Each category contains subfolders for individual problems, along with their respective solutions. The structure is designed for easy navigation and reference.
datalemur-datascience-interview-solutions/ |-- sql/ | |-- easy/ | | |-- solution1.psql | | |-- solution2.psql | |-- medium/ | | |-- solution1.psql | | |-- solution2.psql |-- statistics/ | |-- easy/ | | |-- solution1.py | | |-- solution2.py | |-- medium/ | | |-- solution1.py | | |-- solution2.py |-- python/ | ... |-- probability/ | ... |-- machine-learning/ | ...
Contributions to this repository are welcome! If you have a better solution, additional explanations, or want to add a new problem, feel free to submit a pull request.
This repository is licensed under the MIT License, allowing for both personal and commercial use of the provided code. See the LICENSE file for more details.