Tensorflow Recommended System Specifications

What are the minimum system requirements for executing a simple project in Tensorflow?

UPDATE 2020-01-17 : Try out free online GPU instances. For example colab.research.google.com is one such site and kaggle.com is another! No GPU or local install needed!

I agree with @mad-wombat, there are no minimum requirements to use a CPU for tensorflow.

You said that you are interested in image recognition. With your hardware you could run the MNIST for beginners or the advanced MNIST examples.

Try it out! Tensorflow.org even suggests starting with CPU-only when you first try.

When you become more ambitious and want to do larger projects you'll need to take into consideration how much data you are trying to put into memory. If you are using a CPU or GPU then you'll care about RAM or GPU Memory (respectively), but it certainly isn't a roadblock to starting. Additionally, many people just tune the amount of data stored in memory by doing some of the following :

• store fewer training examples in memory at one time. Many online examples (like MNIST) start by loading all images into memory first, then iterating on them. This just isn't possible with very large data sets no matter the hardware size. The solution is to stream the data through the network.
• use smaller minibatch sizes. Of course I recommend using minibatch sizes of 10 to 100, but depending on your image size and number of hyper parameters, you may have to tune this to something lower, but you'll only find that through some trial and error. In the beginning, I wouldn't worry about it.

But you don't have to worry about this when you are starting! - Just install Tensorflow, walk through the tutorials, and get a feel for it. All the tutorials work just fine on GPU!

I do most of my initial testing and coding on a CPU only machine with limited RAM and it works just great.

Good Luck!

Minimum required hardware component to install tensorflow-gpu in python

TensorFlow (TF) GPU 1.6 and above requires cuda compute capability (ccc) of 3.5 or higher and requires AVX instruction support.

https://www.tensorflow.org/install/gpu#hardware_requirements.
https://www.tensorflow.org/install/pip#hardware-requirements.

Therefore you would want to buy a graphics card that has ccc above 3.5.
Here's a link that shows ccc for various nvidia graphic cards https://developer.nvidia.com/cuda-gpus.

However if your cuda compute capability is below 3.5 you have to compile TF from sources yourself. This procedure may or may not work depending on the build flags you choose while compiling and is not straightforward.
In my humble opinion, The simplest way is to use TF-GPU pre-built binaries to install TF GPU.

To answer your questions. Yes you can use TF comfortably on i5 with 4gb of graphics card and 8gb ram. The training time may take longer though, depending on task at hand.

In summary, the main hardware requirement to install TF GPU is getting a Nvidia graphics card with cuda compute capability more than 3.5, more the merrier.
Note that TF officially supports only NVIDIA graphics card.

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