diff --git a/README.md b/README.md
index f649a25..bd3a162 100644
--- a/README.md
+++ b/README.md
@@ -30,6 +30,17 @@ pip install ethome-ml
 
 `ethome` has been tested with Python 3.7 and 3.8. 
 
+### Conda environment
+
+Note that dependencies have tried to be kept to a minimum so that `ethome` can work easily alongside other programs that may be part of your behavior analysis pipeline (e.g. `DeepLabCut`) -- thus you can try running the `pip install` line above in an existing virtual environment. 
+
+That said, you may want a separate environment for running `ethome`. A conda environment can be created with the following steps: 
+
+1. Download the conda environment yaml file [ethome-conda.yaml](www.google.com)
+2. (From the location you downloaded the yaml file) Create the environment: `conda env create -f ethome-conda.yaml`
+3. Run `conda activate ethome`
+3. And finally `pip install ethome-ml`
+
 ## Quickstart
 
 It's easiest to start with an NWB file, which has metadata already connected to the pose data. 
diff --git a/conda/ethome-conda.yaml b/conda/ethome-conda.yaml
new file mode 100644
index 0000000..e79c879
--- /dev/null
+++ b/conda/ethome-conda.yaml
@@ -0,0 +1,23 @@
+name: ethome
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - python=3.8
+  - setuptools>=42
+  - wheel
+  - numpy
+  - pandas>=1.5.0
+  - scikit-learn
+  - tqdm
+  - protobuf
+  - tensorflow==2.9.0
+  - typeguard
+  - tensorflow-addons
+  - typing
+  - matplotlib
+  - umap-learn
+  - scikit-image
+  - dill
+  - pynwb
+  - ipywidgets