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.
Google’s TensorFlow is an open-source versatile platform that is used for building machine learning and deep learning models for the cloud, mobile, web, and desktop solutions. It’s considered one of the best frameworks for data science and it’s been heavily used by some of the most successful business behemoths from various industries such as Airbus, Intel, Twitter, Coca-Cola, eBay, Snapchat, PayPal, and many others. Many small or medium businesses can also benefit greatly from TensorFlow due to its flexibility and ease of use.
You can input various data quite easily—from images and graphs to SQL and due to the C and C++ backend TensorFlow runs pretty fast.
As an example, Airbnb data scientists use the framework to create deep learning models to effectively categorize listing photos as they are the key to picking up the right place to stay during vacation. It helped the company to create a solution that would classify the room type to increase user experience and make sure that the information provided by the host.
A Python-based framework Pandas is a great tool for data analysis and manipulation. Originally, it was developed by AQR Capital Management, a company in the financial sector. And which industry knows more about data than finance? But now it’s an open-source platform with contributors from all over the world.
Pandas is perfect for data preparation and wrangling and dealing with messy, unstructured, and unlabeled data.
Among its users, you can find Delivery Hero, Tesla Motors, NVIDIA, Target, and a lot of companies use Pandas in various sectors from finance, statistics, engineering, and web analytics to neuroscience, marketing, and many more.
Created by David Cournapeau in 2007, Scikit-learn is now a Python library that can be used for creating outstanding data science projects. It includes a lot of machine learning tools for data mining and data analysis. It’s used for a variety of purposes—to identify spam email, analyzing stock pricing and customer data, etc.
Many companies are using Scikit-learn at the moment such as Spotify, J.P. Morgan, Evernote, Booking.com, MARS, and a lot more. For instance, Spotify users models based on the library for song recommendations and booking.com uses machine learning algorithms for a wide number of reasons:
- fraud detection
- service agent reservation
- destination recommendations
- hotel recommendations
Scikit-learn is an easy and ready-to-use tool for various data science projects and tasks.
Keras is one of the best data science frameworks for your projects. It’s used by Netflix, Uber, Freeosk, Wells Fargo, ASOS.com Limited, Yelp, and NASCENT Technology. Its deep learning frameworks are easy to use, which makes it much easier for you to try different data science ideas. For instance, you can build neural networks without any hitches.
Moreover, Keras was listed as the number one deep learning tool on Kaggle, a community of data scientists by Google.
Facebook’s PyTorch is one of the best machine learning frameworks you can find for data science projects. PyTorch is easy to use due to its dynamic computational graphs, API simplicity, efficiency, and ease of use. You can easily train models to solve many tasks—for research, production, object detection,
Microsoft, Stanford University, Salesforce, and Udacity are among the large users of the framework.
With these five top frameworks for data science, you can create truly amazing projects. TensorFlow, Pandas, Scikit-learn, Keras, and PyTorch are only a fraction of frameworks that can help you build outstanding solutions to meet your business challenges. They are all used by big and small corporations and deserve your attention.
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