Introduction

"How many data science projects have you completed up to this point?" - In data science interviews, this is a relatively frequently asked question. This is usually the key question in the interviews for both data analyst and data scientist positions. This is more applicable if you're new to data science or only recently became interested in it.

Simply taking classes or earning credentials is insufficient. Nearly everyone nowadays has credentials in different fields of data science. If you don't include any relevant work experience, it doesn't improve the worth of your CV.

And that's why open-source data science initiatives are so important in this area. Interviewers adore candidates who take on these tasks and produce answers. This demonstrates your interest, passion, and curiosity for the subject. Including data science projects on your resume will increase your likelihood of landing a job.

Open Source Data Science Projects

Below are some of the best Open Source Data Science projects that you can try at home or in your study/work space. It will enrich your understanding of the subject and help you land in a well-paying job.

1.      Facebook AI’s DEtection TRansformer (DETR) - The most exciting open-source project launched recently is without a doubt DETR by Facebook AI. It is pretty striking that it has amassed approximately 3,000 stars in just one week. Short for DEtection TRansformer, DETR has the potential to revolutionize the field of computer vision. This framework offers a fresh and effective way to handle object detection issues. And DETR is incredibly quick and effective, making it the ideal tool for data scientists. You may use the DETR model without installing any libraries because it is pretty straightforward. DETR treats an object detection problem as a direct set prediction problem with the help of an encoder-decoder architecture based on transformers.

2.      Real-Time Image Animation - The Real-Time Image Animation project is another intriguing open-source project involving computer vision. This enables real-time picture animation using OpenCV, as the name would imply. The project's model imitates the person in front of the camera's emotion and adjusts the image as necessary. It's a fantastic application of computer vision, and we'll definitely test it out internally. Numerous industries will use this kind of project, including fashion, retail, marketing, and advertising.

3.      OpenAI’s GPT-3 - This is one of the most recent Natural Language Processing (NLP) frameworks, called GPT-3, open-source after making a splash with GPT-2 and creating a media frenzy around it. Simply put, the GPT-3 NLP model is the biggest of its type. It is enormous - almost 350GB in size - and has 175 billion parameters. You read that right. Due to its high cost (training it cost over $12 million), GPT-3 is almost among the most expensive models ever created. The fact that language models need a lot of data to train on tasks that people can master in a matter of seconds is not a secret. Advance: GPT-3. Scaling up language models significantly enhances task-agnostic and few-shot results, as demonstrated by OpenAI in the official publication outlining the inner workings of GPT-3

4.      Real-Time Audio Analysis using PyAudio - This Python module, developed and distributed by Xander Steenbrugge, a renowned speaker at the last two DataHack Summits, allows us to carry out real-time audio analysis. The Real-Time Audio Analysis with PyAudio is a straightforward Python package that does real-time audio analysis by extracting and visualizing FFT features from a live audio stream using PyAudio and Numpy. Here, FFT refers to the Fast Fourier Transform. It opens up a large range of problems that you may deal with, making it a fantastic tool to have in your data science toolbox.

5.      Machine Learning Visuals - This project is a great way for Data Science professionals to communicate. An open-source cooperative project called ML Visuals was created to assist the data science community in comprehending and developing technical communication. You may create the ideal presentation or research paper with the aid of the many images, templates, and figures available in this outstanding collection. The fact that everything for this project is included on Google Slides is its finest feature.

Conclusion

A data science project is a way to put your knowledge into practice. You can put your knowledge of data collection, cleaning, analysis, visualization, programming, machine learning, and other related topics to use in a typical open source data science project. It aids in applying your abilities to tackle difficulties in the actual world. The aforementioned projects will help you get spotted by interviewers more efficiently. Although, there are certain ed-tech platforms that help in the process of allotting real-time projects to students so as to help them make their portfolios better and be experienced as data science students and enthusiasts. For instance, the Data Science course in Bangalore with 100% Job guarantee by Skillslash  prioritizes project experience as well as detailed understanding of the subject. Therefore, make an informed decision and get trained from the best platform with the best data science projects.

Written by -

Arpita Deb