Creating and deleting Directory - 13 advanced practical Examples
mkdir F1
Creating directory at the current location using relative path
mkdir /home/user/F2
Creating directory at the current location using absolute path
mkdir /opt/F3
Creating directory at any location using absolute path
mkdir F4 F5 F6
Creating multiple directories at the current location
mkdir –p F7/F8
Creating parent and child directives at the current location
mkdir –m 751 F9
Set the directory permissions while creating the directory
mkdir –v F10
To display the verbose message while creating directory
mkdir --version
To check the mkdir version
rmdir F1
Remove directory at the current location using relative path
rmdir /home/user/F1
Creating directory at the current location using absolute path
rm -rf /etc/FolderName
Deleting directory having the contents (files and folders)
rm –i F1.txt
Creating multiple directories at the current location
rmdir –p F7/F8
Removing nested parent and child directives at the same time

cd Folder-Name
Going inside a directory from current directory using relative path
cd /home/user/Folder-Name
Going inside a directory at the current directory using Absolute Path
cd ..
Going back to the parent directory from the current location
cd ../user2
Going inside a directory which is located inside the parent directory
cd ../../
Move 2 directories back from current location
cd ~ OR cd OR cd $home
Move to home directory of logged in user from any location
cd /home/user*
Going inside a directory whose name initial is “user….”
cd /home/user?
Going inside a directory whose name initial is “user?”
cd -
Going back to the previous working directory
cd . OR cd ./
Going to the current working directory (do nothing)
cd /
Changing the directory to root of the System
cd /etc
Going to any directory using an absolute path

cp command to COPY Files and Directories in Linux - 14 useful and advance Examples:

cp file1 ./F2/
Copy file1 to parent folder F2
cp file1 ./F2/file1
Copy file1 to parent folder F2 same as pervious example
cp file1 file2
Duplicate file1 with new name file2 at same location
cp file1 /home/ec2-user/file1
Copy file to another absolute location inside ec2-user
cp /home/ec2-user/file1 file1
Copy file from another location ec2-user and copy it in current terminal directory location.
cp file1 file2 file3 ./F2/
Coping multiple files (3 files) using single command
cp –p file1 ./F2/file1
Preserve mode, ownership and timestamp while copying file
cp –r F5/* ./F2/
Copy all files and folders iteratively (recursively)
cp –v file1 ./F2/
Display the Verbose output during the copy of file1
cp –v –u file1 ./F2/file1
Copy file only if the source file is newer then existing destination file.
cp –n file1 ./F2/file1
Copy file from another location without overwriting if the file already exists there.
cp –s file1 ./F2/
Create symbolic link (shortcut) of the file at destination.
cp –f file1 ./F2/
Copy the file forcefully at the destination location.

mv command to MOVE Files and Directories - 8 useful and advance Examples - SP 10:

mv file1 ./F2/
Move file1 to parent folder F2
mv file1 ./F2/file1
Move file1 to parent folder F2 same as pervious example
mv file1 file2
Rename file1 with new name file2 at same location
mv file1 /home/ec2-user/file1
Move file to another absolute location inside ec2-user
mv /home/ec2-user/file1 file1
Move file from another location ec2-user and copy it in current terminal directory location.
mv file1 file2 file3 ./F2/
Moving multiple files (3 files) using single command
mv F5/* ./F2/
Move all files and folders iteratively (recursively)
mv –v file1 ./F2/
Display the Verbose output during the moving of file1

cat command to Create & Update Files in Linux - 12 useful and advance Examples:

cat file1
Display the content of the file1 as read-only

Create new file2 and open it in edit mode in terminal

Open the file named file2 in append mode
cat file1 file2
Display contents of multiple files file1, file2 as read-only
cat –n file1
Display the line number with the content of the file1

Copy the contents of the file1 to file3 as new file

Append the contents of file1 to file2

Copy contents of file1, file2, file3 to file4.

Append file1, file2 to file3.
cat –e file1
Display $ at the end of every line in file1 contents

Display contents of large file with
Cat -T file1
Display the contents of file1 with each line tab separated

vi command to Create & Update Files in Linux | 18 useful and advance Examples:
vi file1
Open the existing file or create a new file named file1
Press ESC key
To shift to Control / Command Mode
Press i or a key
To shift to Edit Mode
:w
To Save/write the file but make sure you are in Control/Command mode.
:q
To Close/Quit the file but make sure you are in Control/Command mode.
:wq OR zz
To write and close the file but make sure you are in Control/Command mode.
:q!
Enforce to Close/Quit the file without saving the file but make sure you are in Control/Command mode.
:e!
Read the original file again to start over without saving the changes
$
Go to the end of the line
^
Go to the start of the line
W
Go to the next word
B
Go to the previous word
Shift + G
Go to the last line of the File
10 Shift + G
Go to the 10th line of the file
Y
Copy (Y2W copy 2 words, Y2J copy 2 lines
P
Paste the copied contents
D
Cut the selected letter
X
Delete the character under the curser

Hello everyone and welcome to another video blog on the computer graphics video lecture series
and today we are going to cover how different fields are interlinked with each other which are like computer graphics, computer vision, artificial intelligence, machine learning, and deep learning.
Let's start with the computer graphics, it is an important field where the computers use to take an input of any defined model algorithm textual information or even graphical information or data and it used to do some processing and produce an improved or enhanced is a new graphical visualization.
Next is computer vision, where the computer is used to take input of an image or graphical data and it's used to produce some sort of information that can be used for the decision making analysis or to do some sort of further processing. In computer graphics, the output always used to be another graphical thing or a new graphical model or design, while in the computer vision the input used to be graphical data in the form of video or visual information images, and the output used to be some decision information. So, both fields are almost opposite to each other in terms of producing the output and in terms of taking the input.
While, how these two domains are linked with the other domains like artificial intelligence, machine learning, and deep learning before going to that part I will discuss these three fields.
Artificial intelligence is the main field where tries to make the computing device much powerful that they will start acting like the human brain and they will start making the decisions on their own based on the trained models or based on the set of rules.
Machine learning is a subfield of artificial intelligence where we use to let the machines learn the way our brain used to learn like at the start, we used to train our brain by feeding some sort of information. In the same way, we let the computers get trained by giving a large amount of data, and then we used to give some new data in order to produce the output for analysis or decision making.
Deep learning is a subfield of machine learning where the prediction rates are much higher as compared to the other typical machine learning algorithms. By using deep learning algorithm, the input training data need to be extremely high and we used to let deep learning algorithms extract the features by their own and then use those features to take the decision.
The artificial intelligence has sub-field machine learning and machine learning has sub-field deep learning. Now how these three domains are interlinked with the computer graphics and computer region, if we see in computer graphics, we use to let the computers generate new graphics and how we can generate those graphics? Of course, we need to have some sort of algorithms running in the background. One option is we can generate graphics by direct user interaction with graphical software and doing the arrangements of different graphics and doing some processing by using photoshop or AutoCAD. The other option is that we can use the programming algorithms and we will define a set of rules and the new produced model will be acting based on those defined set of rules or defined models or defined algorithms. Here the idea of artificial intelligence and machine, learning and deep learning comes, where we can generate the new graphical images by applying these techniques.
I can give you several examples like we can do image enhancement and we can remove the noise from the images by using artificial intelligence and machine learning algorithms. In the same way, in order to extract different objects from the images or from the graphics, we can again apply artificial intelligence and machine learning. Another example like we want to merge our combined different objects or different graphics together to act collectively in a single new graphical image or graphical representation. In this case, again we can apply artificial intelligence or machine learning.
If we will apply machine learning and artificial intelligence, manual work will be reduced and even we can get better representation if we will have a better-defined model for the new graphical images. Therefore, we can say, all these fields are interlinked somehow because all of them are using computing devices in order to generate some sort of representation or results or in order to take decisions similarly.
For the computer version, a graphical image is used to be fed to the computer in order to produce some sort of decision making, recognition, or prediction. So, in that case, again artificial intelligence is the one which is actually used at the backend and the prediction are being done by using the rule-based methods or by using the machine learning algorithms.

Hello everyone and welcome to another video blog on the computer graphics lecture series and today we are going to cover the history of computer graphics.

I will start with the history of visual representation. Humans have always been visual creatures. If we will see almost every living animal, they use to have eyes that can be used to see or recognize the objects or visual information. Humans are always visual creatures and we used to recognize visual things or objects by using our eyes, even before speaking language was created. Here is an example where we can see an Indonesian cave painting that is around 38,000 years BCE and this graphical painting is around 40 000 years old now.

Let's talk about computer graphics history.

We will start from the 1960s because it is the same time when the first computer was invented. In the same days, the researchers started to think that how they can use computers to generate the graphics to present the visual information. The term computer graphics itself was coined in the same time period in the 1960s by William Fetter and the first time the video games were introduced. Some of the famous video game names are like space-war, tennis for two, pong.

In the given image, you can see that is an example of a video game Star Wars that was invented in the 1960s, and over here they tried to use some sort of graphical data over the screen. At the same time era, most of the researchers started to work and propose different techniques that can be used for computer graphics.

Let's move to the 1970s, practical implementation of modeling techniques was started because at that time that the computers started to become enough powerful by using the large-scale integrations. At this time era, different techniques including rendering, texture mapping, and hidden services were used to generate the graphics as you can see over here the second image which is generated by the computers by applying these techniques.

In the 1980s, a lot of work has been done in this era. Modernization and commercialization of computer graphics started. a lot of work was done in order to use the computer graphics for commercial purposes, to have more powerful video games, animated movies, and to enhance the existing graphical data to present it in a better way. Computer graphics-based movies such as Star Wars were started in this time period. This time era can be also known as the golden era of video games as sales of millions of video systems by Atari, Nintendo, Sega, and other companies were done by introducing these games to the young audience. Therefore, we can say like the 1980s is the actual time when computer graphics started to be used for commercial purposes as before that most of the work was being used for the research and non-commercial use.

Let's talk about for 2000s era where computer modeling started to be used on a large scale for commercial activities. At the same time, 3D video games were invented and being used by a very large number of audiences. Computer graphics were also adopted for tv commercials, cinema and video games. In this time period many sophisticated CPUs and more powerful GPU hardware were invented for computer graphics which helped a lot for a computer graphics field to flourish. In this time period, new gaming devices were also invented such as PlayStation 2, PlayStation 3 by Sony, and Xbox by Microsoft which got very popular.

Now let's talk about the current situation of computer graphics. Now we can say that computer graphics has been matured. Nowadays the movies and video games are being made in ultra HD or 4K graphics which are very good. Although to generate these graphics required a lot of processing power but because of the more sophisticated hardware available in terms of GPUs, we can process these ultra HD movies and games on our computing devices.

A new concept has been emerged with the name of virtual reality and augmented reality where we try to see the object by using the virtual environment. A lot of research is going on in this field. For example, Facebook is doing a lot of development and research in the field of virtual reality and augmented reality. They already introduced Oculus Rift for commercial use.




That's it for the first blog session and in the next session, we will discuss the history of the computer graphics. Please subscribe to my YouTube channel and don't forget to share this blog and YouTube video.

Welcome to another video blog on the computer graphics lecture series. In this blog, we're going to discuss that computer graphics is a homogeneous field because in computer graphics we use similar objects with different properties to make or generate the computer graphics.
In computer graphics, we used to make 2D shapes by combining or merging similar objects with different properties such as lightning effects materials and texture mapping. This sort of information as you can see in this image. It has been created by using the computer graphics and all the things appearing over here are actually computer-based.
Next is 3D models which are also used to be generated by using computer graphics with different properties and different sets of objects in different ways of representation. As you can see in the model of the building, it has been actually made by computer graphics. These 3D models are further enhanced by manipulating the different properties of computer graphics for the better representation of these models.
Modeling material properties are being used in the computer graphics for better representation to look like the same as the real-world objects.
Next is realistic lighting environments, that is being used in computer graphics to enhance the image representation. Texture mapping is another property that is being used in computer graphics for better representation or better visualization of the generated graphics. First, the graphics are being created by using the defined models and then the texture mapping and lighting used in order to have a better representation of those images. As you can see over here an image or a graphics that is without texture mapping and after the texture image mapping of the Dinosaur.
Physically-based simulations of motions is another important property that is widely used for computer graphics in order to replicate the different objects with the physical movements. Especially in the field of animation and video games, this property is the most widely used. In the figure, you can see that the computer graphic generated shared object has been used repeatedly with different angles, different lighting, and shades effects.

That's it for this session and if you have any questions you can write down in the below comments and you can I will try to answer you as possible. Please subscribe to my YouTube channel and don't forget to share this blog and YouTube video.

What is Artificial Intelligence?

- Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.
- Development and Improvement of AI systems to have the same level of Intelligence as humans have.
- Example: Number Plate Detection as AI preceptive

History of Artificial Intelligence

AI History: Early Work (1900-1930):
Main Researchers (Representatives)
George Boole (Boolean Symbols)
Alfred Whitehead (Logic and Reasoning)
Bertrand Russell (Principia Mathematica)
Main Contributions
Boolean Algebra
Mathematical Logic and Reasoning
Principia Mathematica

AI History: Early Work (1930-1950):
Main Researchers (Representatives)
Alan Turing (Turing Machines)
Claude Shannon (Boolean Algebra)
Jhon Von Neumann (Computing Model)
Main Contributions
Theory of Computation/Automata (Turing Machine)
Turing Test (To distinguish Machines from Human)
Information Theory
Applications of Boolean Algebra
Von Neumann Model of Computing Machines

AI History: First Wave (1950-1980):
Main Researchers (Representatives)
John McCarthy
Herbert Simon
Marvin Lee Minsky
Edward Feigenbaum
Allan Newell
Main Contributions
LISP – Programming Language
Semantic Network / Frame Network
Expert Systems (Inference Engine and Knowledge Base)

AI History: Second Wave (1980-2000):
Main Researchers (Representatives)
Lotfi Zdeh
John Holland
John Koza
David Rumelhart
Lawarence Frogel
Main Contributions
Neural Networks and Multilayer Perceptron (MLP)
Fuzzy Logic and Fuzzy Systems
Genetic Algorithms and Programming
Applications of Boolean Algebra
Random Trees and Random Forests

AI History: Third Wave (2000-onwards):
Main Contributions (Representatives)
WWW – Internet (Tim Berners-Lee )
Internet of Things (Kevin Ashton )
Cloud Computing (Got popularity in ~ 2010)
Big Data (John ‏Masey)
Deep Learning (Geoffrey Hinton)

Difference between Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Computer Graphics, Digital Image Processing, Natural Language Processing

Relation Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Computer Graphics, Digital Image Processing, Natural Language Processing

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.

Machine Learning (ML) is the study of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so.

Deep Learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Example: In image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters, or faces.

Computer Vision is a field of artificial intelligence that trains computers to interpret and understand the visual world (Images/Videos). Takes an image/video as an input and produces an outcome as a decision. For example, face recognition using the image.

Computer Graphics deals with creating images, animations, videos, with the help of computers by taking numerical data, mathematical models or graphical data.
Video Games
Animations
Drawing on Screen (Paint)

Digital Image Processing is the use of computing machines to process images using different algorithms (AI or non-AI based).
Edge Detection
Image Enhancement
Image Segmentation

Natural Language Processing is the use of computers to manipulate, interpret and understand the human language.
Speech Recognition
Text Translation
Sign Language Recognition

Difference and Relationship between IoT, Cloud Computing, Big Data, and Deep Learning
Relationship between Internet of Things (IoT) and Cloud Computing
Relationship between Cloud Computing and Big Data
Relationship between Big Data and Deep Learning / Machine Learning

The relation between State Space and Search Graph Representation
Search Algorithms
Random Search
Random Search with Open List
Random Search with Closed List
Artificial Intelligence Video Lecture Series

Random Search Step by step Algorithm and Example
ARTIFICIAL INTELLEGINCE
Random Search Example with full details

This workshop is about the introduction of Machine Learning, Deep Learning, their applications, and how the research skills can be build using Machine Learning. The works shop also contains two research-oriented practical demos with the code to generate the results.
This workshop was conducted at Prince Mohammad bin Fahd University.