What Versions of Python Anaconda and TensorFlow Work Best Together on Windows 81

In this blog, we will learn about the significance of employing appropriate tools for data science tasks. Among the widely used tools for machine learning and deep learning tasks are Python, Anaconda, and TensorFlow. However, determining the optimal versions to use together, particularly on older operating systems like Windows 8.1, can pose a challenge.

As a data scientist, you understand the importance of using the right tools to get the job done. For machine learning and deep learning tasks, Python, Anaconda, and TensorFlow are some of the most popular and widely used tools. However, it can be challenging to determine the best versions to use together, especially on older operating systems like Windows 8.1.

In this article, we will delve into the compatibility issues between Python, Anaconda, and TensorFlow and recommend the best versions to use together on Windows 8.1.

Table of Contents

  1. Why Version Compatibility Matters

  2. Python Versions

  3. Anaconda Versions

  4. TensorFlow Versions

  5. Best Practices

  6. Conclusion

Why Version Compatibility Matters

Compatibility is crucial for smooth functioning of Python libraries and frameworks. Mismatched versions can lead to errors, decreased performance, and even system crashes. This section will delve into the importance of version compatibility and its impact on your development workflow.

Python Versions

Python is a popular programming language used for various purposes, including data analysis, machine learning, and deep learning. However, not all versions of Python are compatible with all versions of Anaconda and TensorFlow.

For Windows 8.1, we recommend using Python 3.6 or higher. The latest version of Python as of this writing is Python 3.10, but it is not compatible with some older versions of Anaconda and TensorFlow. Therefore, using Python 3.6 to 3.9 is the best option to ensure compatibility with Anaconda and TensorFlow.

Anaconda Versions

Anaconda is an open-source distribution of Python and R that includes a collection of packages for scientific computing and data science. Anaconda can be used to create virtual environments for different Python projects, each with its own set of packages.

For Windows 8.1, we recommend using Anaconda version 2021.05 or higher. This version includes Python 3.8, which is compatible with TensorFlow 2.x. However, if you need to use an older version of TensorFlow, you can create a virtual environment with Anaconda and install the required version of Python and TensorFlow.

To create a virtual environment with Anaconda, open the Anaconda prompt and type the following command:

conda create --name myenv python=3.8 tensorflow=2.4

This command creates a virtual environment named “myenv” with Python 3.8 and TensorFlow 2.4.

TensorFlow Versions

TensorFlow is an open-source machine learning library developed by Google. It is widely used for building and training deep learning models. TensorFlow has two major versions: TensorFlow 1.x and TensorFlow 2.x.

For Windows 8.1, we recommend using TensorFlow 2.x. This version supports Python 3.6 to 3.9 and is compatible with Anaconda version 2021.05 or higher. TensorFlow 2.x includes many new features and improvements over TensorFlow 1.x, making it a better choice for most machine learning and deep learning tasks.

To install TensorFlow 2.x, you can use pip, the Python package manager. Open the command prompt or Anaconda prompt and type the following command:

pip install tensorflow

This command installs the latest version of TensorFlow 2.x available on PyPI.

Best Practices

Choosing the right combination of Python, Anaconda, and TensorFlow versions involves considering various factors to ensure a smooth and efficient development environment. Here are some best practices to guide you in making informed decisions:

Stay Informed

Regularly check the official documentation for Python, Anaconda, and TensorFlow for updates and compatibility information. The development landscape evolves, and staying informed ensures that you’re aware of the latest recommendations and potential issues.

Use Virtual Environments

Create isolated virtual environments for your projects using tools like conda. This practice helps avoid conflicts between project dependencies and ensures that each project has its own dedicated environment, making it easier to manage and reproduce your development environment.

Monitor Community Feedback

Engage with the developer community and forums to gather insights and feedback on specific version combinations. Community feedback can provide valuable information about common issues, workarounds, and best practices.


In conclusion, if you are using Windows 8.1 for machine learning and deep learning tasks, we recommend using Python 3.6 to 3.9, Anaconda version 2021.05 or higher, and TensorFlow 2.x. These versions are compatible with each other and provide the best performance and stability for your projects.

About Saturn Cloud

Saturn Cloud is your all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, and more. Request a demo today to learn more.