Update README.md

Author: RuneDK93

README.md

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 #  $\texttt{TAU}$: telluric-autoencoder
 This is a pytorch based code for $\texttt{TAU}$ (Telluric AUtoencoder), which can be used to perform quick and high accuracy telluric correction of astrophysical spectral data. See the paper for more details.
 
- $\texttt{TAU}$ is based on a constrained autoencoder structure, which learns a compressed representation of the training data. The compressed representation can be used to extract intepreteable componenets. Some of these components relate to telluric absorption of light in the atmosphere of Earth. The extracted telluric spectrum can be applied to new observations to perform accurate telluric correction at low computational expense.
+ $\texttt{TAU}$ is based on a constrained autoencoder structure, which learns a compressed representation of the training data. The compressed representation can be used to extract intepreteable components. Some of these components relate to telluric absorption of light in the atmosphere of Earth. The extracted telluric spectrum can be applied to new observations to perform accurate telluric correction at low computational expense.
 
 ## Performing telluric correction
 Inspect the *AE_correction.ipynb* notebook for a guide on performing telluric correction. Here $\texttt{TAU}$ uses the extracted telluric spectrum on new observations to perform telluric correction. Telluric correction is performed with the *telluric_fit* function from *correction.py*.