Machine learning is the subfield of artificial intelligence that deals with training an agent to perform a task or a set of tasks, without the need to be explicitly programmed. The learning process is made possible as the agent uses previously observed data to make decisions, while at the same time, it receives feedback for its actions and as a result, it is able to improve its performance on future tasks.
Different subcategories of machine learning algorithms are defined according to the way the agent receives its feedback. The three main subcategories are: supervised learning, unsupervised learning and reinforcement learning [30], however, this distinction is not absolute, as some algorithms have characteristics from more than one of these …show more content…
The network takes as input a 32×32 raw image that represents a letter or a number and it is able to efficiently detect which letter or number is represented in the image. This model outperformed almost every other machine learning model on this task at that time and it popularised the use of deep convolutional neural networks.
6 Introduction
1.4 Low-density lipoprotein
As the current project deals with the application of computer science methods to tackle a problem from the field of cell biology, it would be appropriate at this point to provide some background information about the objects of interest of this study.
Plasma lipoproteins are biochemical assemblies, consisted of lipids and proteins and their main functionality within the body is to transport the major lipids of plasma, like cholesterol esters, phospholipids, triglycerides, free cholesterol and free fatty acids, outside of cells.
Based on their physical and chemical properties, lipoproteins are classified as: high-density lipoproteins (HDL), low-density lipoproteins (LDL), intermediate-density lipoproteins (IDL), very low-density lipoproteins (VLDL) and ultra low-density lipoproteins or chylomicrons
(ULDL). [10]
Low-density lipoprotein particles, which are more specifically the objects of
Different subcategories of machine learning algorithms are defined according to the way the agent receives its feedback. The three main subcategories are: supervised learning, unsupervised learning and reinforcement learning [30], however, this distinction is not absolute, as some algorithms have characteristics from more than one of these …show more content…
The network takes as input a 32×32 raw image that represents a letter or a number and it is able to efficiently detect which letter or number is represented in the image. This model outperformed almost every other machine learning model on this task at that time and it popularised the use of deep convolutional neural networks.
6 Introduction
1.4 Low-density lipoprotein
As the current project deals with the application of computer science methods to tackle a problem from the field of cell biology, it would be appropriate at this point to provide some background information about the objects of interest of this study.
Plasma lipoproteins are biochemical assemblies, consisted of lipids and proteins and their main functionality within the body is to transport the major lipids of plasma, like cholesterol esters, phospholipids, triglycerides, free cholesterol and free fatty acids, outside of cells.
Based on their physical and chemical properties, lipoproteins are classified as: high-density lipoproteins (HDL), low-density lipoproteins (LDL), intermediate-density lipoproteins (IDL), very low-density lipoproteins (VLDL) and ultra low-density lipoproteins or chylomicrons
(ULDL). [10]
Low-density lipoprotein particles, which are more specifically the objects of