SubhadityaMukherjee

\tableofcontents

SubhadityaMukherjee

\begin{titlepage}
   \begin{center}
       \vspace*{1cm}

       \textbf{Thesis Title}

       \vspace{0.5cm}
        Thesis Subtitle
            
       \vspace{1.5cm}

SubhadityaMukherjee

\section{Equations}
We can have three types of these - An inline equation : $2x+3 = 10$, or a proper block , $$2 \sin(x)+10 = 100$$ or a long form one such as this.
\begin{equation}
E[g^{2}]_{t}= 0.9E[g^{2}]_{t-1}+ 0.1g^{2}_{t}\\
\theta_{t+1}= \theta_{t}- \frac{\eta}{\sqrt{E[g^{2}])_{t}+\epsilon}}g_{t}
\end{equation}

SubhadityaMukherjee

\begin{lstlisting}[language=Python]
import numpy as np
print(np.random.rand(10))
\end{lstlisting}

SubhadityaMukherjee

\usepackage{listings}

SubhadityaMukherjee

\section{Formatting}
This \textbf{will be bold}, then \textit{italic}, and also \textcolor{red}{red}. 

To add a line break, simply add \\
this will be a new line

SubhadityaMukherjee

\begin{figure}[h]
\includegraphics[width=\linewidth]{figures/2560px-PyTorch_logo_black.svg.png}
\centering
\caption{Representation in the Simulation}
\label{fig:colors}
\end{figure}

SubhadityaMukherjee

\section*{What is Computer Vision?}
A study of the techniques used to extract meaning from image or video related data. The applications are endless, starting from face recognition, to self driving cars.
\subsection*{Computer Vision in the field of Deep Learning}
Deep learning has revolutionised the field of Computer Vision by giving it superpowers. The ability to learn from billions of images come as a huge leap forward in the field.
\subsubsection*{A note}
Classicial CV is still very relevant today.

SubhadityaMukherjee

\begin{abstract}
This paper is a short introduction to Pytorch, a deep learning framework. Special focus will be given to applications of Computer Vision. This is a demo paper, and has no particular significance.
\end{abstract}

SubhadityaMukherjee

\title{Computer Vision in Pytorch - A Primer}