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Python: Which Platform Does it Run on?

Python Platforms


A data science platform is a type of software that contains multiple technologies for machine learning, advanced analytics, and data science projects. It is a set of software tools and frameworks aimed at helping data scientists and analysts with data analysis, modeling, and other tasks involved in extracting insights from data. These types of projects are frequented by multiple issues with the data, such as incorrect, incomplete, inaccurate, or irrelevant data, in each step of the analysis, cleaning, and modeling process. Its purpose is to provide a unified working environment for data scientists, streamline the data analysis process, and improve the efficiency and effectiveness of data-driven decision-making.

A practical example of a data science platform:

Let’s say that you work for a retail company and your goal is to improve customer satisfaction by analyzing customer feedback data. To do this, you’ll need to perform various tasks such as importing and cleaning data, exploring and visualizing data, building, and training predictive models, and deploying those models in a production environment.

To accomplish these tasks, you could use a data science platform like the Anaconda platform. Here’s how you might use Anaconda platform to analyze customer feedback data:

Top Data Science Platforms for Python Language

1.     Anaconda:

Anaconda provides a simple way to perform data science and machine learning analytics using Python/R on a single machine. Using Anaconda’s Navigators, you can easily search for packages on an anaconda cloud or local directory and then install and update when needed.

2. is an open-source and free-to-use platform that aims to simplify AI and ML. Driverless AI is an optimized version that utilizes GPU acceleration to achieve up to 40 times faster automatic machine learning. Feature engineering is a technique that skilled data scientists use to obtain the most accurate outcomes from algorithms, and it uses an algorithm and feature transformation library to automatically create new, valuable characteristics for a given dataset.

3.     TensorFlow

TensorFlow is a comprehensive platform that can be used to deploy machine learning pipelines. It includes a configuration framework and shared libraries that can be employed to combine essential components needed to define, deploy, and analyze machine learning systems.

4.     SageMaker

SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale. Python is one of the most popular languages for data science and machine learning, and SageMaker provides built-in support for Python 2 and 3. Users can run Jupyter notebooks, which are a popular tool for data scientists, using Python within SageMaker.

5.     Neptune

Neptune is a tool designed for managing machine learning experiments that is both lightweight and versatile. It facilitates the tracking of experiments and the management of model metadata and can integrate with a variety of frameworks. With a stable user interface, Neptune is highly scalable.

6.     Iguazio

Iguazio is a tool that can automate machine learning pipelines. It streamlines the development process, improves performance, promotes collaboration, and tackles operational hurdles. It is a complete data science workbench package that includes Jupyter Notebook, integrated analytics models, and Python packages.

7.     PyTorch

Developed by Facebook’s AI research team, PyTorch is designed to provide flexibility and ease of use for researchers and developers. It has a dynamic computational graph, which means that the graph is created on-the-fly as the code is executed. Additionally, PyTorch has a strong focus on GPU acceleration, which allows for efficient training of deep neural networks on large datasets.

8.     Databricks

Databricks is a cloud-based platform that provides a collaborative environment for data science teams to work together on large datasets using Python and other programming languages.

9.     Dataiku

Dataiku is an AI and machine learning platform that provides a visual interface for building machine learning models using Python, R, and SQL.

10.  Domino Data Lab

Domino Data Lab is a data science platform that provides a collaborative environment for building and deploying machine learning models using Python, R, and other programming languages.


We have effectively covered the effects of data science platforms and how they can solve a variety of real-world problems. Data scientists and researchers can concentrate more on analytics and research by using the potential of automation in data science than maintaining code or working on creating code. Enrolling in Sambodhi’s thorough Python Training Course would be a terrific place to start if you’re looking to jump start your career in the tech sector of data science. With the help of this course, you will acquire all the practical skills for employment and seize the greatest possibilities available in your industry. For more information, visit Education Nest.

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