Updated the introduction

projectsynopsis/project-synopsis.tex

@@ -58,32 +58,42 @@
     \section{Introduction}
     % This section should contain an introduction to the problem aims and objectives (0.5 page)
 
-    Image classification is a useful task in many areas. 
+    The aim of this project is to create a classification service that has 0
-    Currently, there exists a few systems that can do image classification, for example Google's Vision API or Amazon's Rekoginition, which tend to be for more general object recognition and labelling. 
+    requires zero user knowledge about machine learning, image
-    My plan is to create a generalized image classification solution to automatically generate models with the input dataset with minimal user interaction.
+    classification or data analysis.
-
+    The system should allow the user to create a reasonable accurate model
-    The system should also allow the user to create expandable models, where the number of classes is not known at the moment of that the model is created. 
+    that can satisfy the users' need.
-    Therefore, the system should allow the user to create models that can expand and reduce.
+    The system should also allow the user to create expandable models;
-
+    models where classes can be added after the model has been created.
-    This should be done in an efficient, and a change in the number of classes should not result in the entire model retraining.
 
     \subsection{Aims}
-    The project aims to create a system that allows users to create classification models with 0 knowledge of machine learning or data science.
+    The project aims to create a platform where users can create different types of classification models without the users having any knowledge of image classification.
-    The system should also allow the user to expand the models to include new classes if the user wishes, after the model has been trained.
 
     \subsection{Objectives}
-    This project objectives are to: 
+        This project's primary objectives are to: 
-    \begin{itemize}
+        \begin{itemize}
-    \item Create a system to automatically create and train models
+            \item Create platform where the users can create and manage their models.
-    \item Create a system to automatically expand and reduce models without fully retraining.
+            \item Create a system to automatically create and train 
-    \item Create a system to automatically to merge modules to increase efficiency
+            \item Create a system to automatically create and train models
-    \end{itemize}
+            \item Create a system to automatically expand and reduce models without fully retraining the models.
-
+        \end{itemize} 
+        This project extended objectives are to:
+        \begin{itemize}
+            \item Create a system to automatically to merge modules to increase efficiency
+            \item Create a system to distribute the load of training the model's among  multiple services.
+        \end{itemize}
     \section{Literature Review}
     % 1 page of background and literature review. Here you will need to references things. Gamal et al.~\cite{gamal} introduce the concept of \ldots
+
+    \subsection{Alternatives to my Project}
     There currently exist systems that do image classification, like Google Vision AI, and Amazon's Rekoginition. 
     Their tools, while providing similar services to what my project is supposed to do, it mostly focusses on general image classification rather than specific image classification, i.e. Car vs Boat, vs, Car model X vs Car model Y.
 
+    \subsection{Creation Models}
+
+    \subsection{Expandable Models}
+
+    \subsection{Merging models}
 
     \section{Technical overview}
     % 1 page of overview. My approach is shown in Figure~\ref{fig:sample}. You can draw the diagram in powerpoint and save the picture