Five Frameworks to Generate Best-in-Class Data Science Projects

John Doe


Data science is definitely going to have a bright future as companies across the globe are becoming more sophisticated in their approaches to dominate in their niches. They want to increase sales, attract new clients, improve customer satisfaction, and earn a few bucks without much difficulty.

For instance, large and small retailers can use data science to predict goods demand during a certain period of time and place or analyze sentiments about a company, product, and service, or brand. Applications of data science in business are numerous. And to make usage of data science easier, there are several data science frameworks that can help you launch any data science project. Here are five picks that will assist your business.

What is a Programming Framework and Why to Use One?

Originally, the first meaning of a framework was a structure that supports or frames something, like in a building. Now, a framework has somewhat broader meaning—it’s a set of rules, beliefs, and ideas that help us solve and approach difficult problems and tasks.

In data science, a programming framework is software that has been already developed that includes reusable functionality so that you could create your projects easily and faster. This is why it’s quite practical to use a framework.

What are the Best Five Frameworks to Use for Data Science Projects?

There are quite a few frameworks available for data scientists to create truly best-in-class projects to turn any data science idea into a reality. And machine learning frameworks can automate processes to boost many businesses. Here’re the best ones you might want to consider.

  1. TensorFlow
  2. Pandas
  3. Scikit-learn
  4. Keras
  5. PyTorch