Why is Tensorflow not recognizing my GPU after conda install?

The tensorflow build automatically selected by Anaconda on Windows 10 during the installation of tensorflow-gpu 2.3 seems to be faulty. Please find a workaround here (consider upvoting the GitHub answer if you have a GitHub account).

Windows only: Python 3.7: conda install tensorflow-gpu=2.3 tensorflow=2.3=mkl_py37h936c3e2_0

Python 3.8: conda install tensorflow-gpu=2.3 tensorflow=2.3=mkl_py38h1fcfbd6_0

@geometrikal solution almost worked for me. But in between installing tensorflow-gpu with conda and installing tensorflow 2.3 with pip, I needed to uninstall the tensorflow parts of the package tensorflow-gpu to avoid conistency warnings by pip. Conda would have uninstalled the whole package. I know Conda does not recommend mixing pip with conda but this is the solution worked that worked and I am tired of spending another day with this issue.

conda create -n tfgpu python=3.7
conda activate tfgpu
conda install tensorflow-gpu=2.1

pip uninstall tensorflow
pip uninstall tensorflow-estimator
pip uninstall tensorboard 
pip uninstall tensorboard-plugin-wit
pip install tensorflow==2.3
pip check

August 2021 Conda install may be working now, as according to @ComputerScientist in the comments below, conda install tensorflow-gpu==2.4.1 will give cudatoolkit-10.1.243 and cudnn-7.6.5

The following was written in Jan 2021 and is out of date

Currently conda install tensorflow-gpu installs tensorflow v2.3.0 and does NOT install the conda cudnn or cudatoolkit packages. Installing them manually (e.g. with conda install cudatoolkit=10.1) does not seem to fix the problem either.

A solution is to install an earlier version of tensorflow, which does install cudnn and cudatoolkit, then upgrade with pip

conda install tensorflow-gpu=2.1
pip install tensorflow-gpu==2.3.1

(2.4.0 uses cuda 11.0 and cudnn 8.0, however cudnn 8.0 is not in anaconda as of 16/12/2020)

Edit: please also see @GZ0's answer, which links to a github discussion with a one-line solution