Introduction
Chapter One: An Introduction to Computer Systems and Networking
Chapter Two: Inside the Computer Systems and Networking Concept
Chapter Three: Computer Systems Network and Security
Chapter Four: Computer System Network: Setting Up Your Own
Chapter Five: IP And Subnetting Explained
Chapter Six: Applying the Concepts of Computer Systems Network
Chapter Seven: Outside the Network Numbers: What Still Matters
Conclusion
Resources:
Introduction
Chapter 1: Black Hat Hacking
Chapter 2: White Hat Hacking
Chapter 3: Grey Hat Hacking
Chapter 4: Networks
Chapter 5: Scripting and Other Tools
Chapter 6: The Different Types of Hacking and How they Work
Chapter 7: How to Protect yourself from Hacking
Chapter 8: Cybersecurity and How it Saves you from being Hacked
Conclusion
Artificial Intelligence
And Life
Introduction
Chapter One: Foundations of AI
Philosophy and Logic
From Life Itself
Psychology and Cognitive Science
Statistics and Probability
From Computer Engineering
Chapter Two: What is AI?
The Turing Test Approach: Acting Humanly
The Cognitive Modeling approach: Thinking humanly
The Laws of Thought Approach: Thinking Rationally
The Rational Agent Approach: Acting Rationally
Chapter Three: Basic Concepts in AI
Data
Information
Knowledge
Intelligence
Artificial Intelligence
Classifications
Association
Decision Trees
Deep Learning
Chapter Four: How Machines Learn
Forms of Learning
Components to be Improved
Representation and Prior Knowledge
Feedback to Learn From
Unsupervised Learning
Reinforcement Learning
Supervised Learning
Semi-supervised Learning
Chapter Five: Machine Learning
Memory-Based Learning
Case-Based Reasoning
Decision Trees
Data Mining and Decision Trees
EPAM
CLS
ID3
C4.5, CART and Successors
Inductive Logic Programming
Neural Networks
Input layer
Output layer
Hidden layer
Unsupervised Learning
Reinforcement Learning
Chapter Six: Big data
Essentials of Big Data
Sources of Big Data
Public sources
Private sources
Building new data from existing data
Using existing data sources
Statistics and Machine Learning
Role of Algorithms
Strategies for Algorithms
Symbolic Reasoning
Brain Modeling
Evolutionary Modeling
Bayesian Inference
Training Data Sets
Representation
Evaluation
Optimization
Chapter Seven: Modern AI
Games
Chess
Checkers
AI at Home
Advanced Driver Assistance Systems
Route Finding Maps
Recommendation Systems
In Medicine
For Scheduling
For Automated Trading
In Business Practices
In Translating Languages
For Facial Recognition
Conclusion
Sources
Introduction
Chapter One: Big Data and Data Science
History of Data Science
Definition of Data Science
Who is a Data Scientist?
How Data Scientists Increase the Worth of a Business
The Technique of Data Science
Impacts of Data Science
Importance of Data Science
Programming Languages Every Data Scientist Should Know
Python
R Language
Java
Scala
SQL
Julia
Matlab
The Data Science Process
The Future of Data Science as a Carrier Choice
Chapter Two: Cyber Security
Introduction
Most Common Cybersecurity Threats
β Trojan horses
β Man in the Middle attacks
Impacts of Cyber Attacks on Business
The financial cost of cyber-attack
Reputational Impact of a Cyber-Attack
Legitimate Impact of a Cyber-Attack
Psychological Impact of Cyber-Attack
Physical Impact of a Cyber-Attack
Social Impact of a Cyber-Attack
How can Cyber-Attacks be Reduced?
Creating responsiveness of cyber-security within an organization
Investing in cyber safety and cyber-security backup
Keeping up to date with all of the safety arrangements and testing the security measures regularly
Chapter Three: Cyber Technology
Features that Must be Present in a Cyber Technology Platform
Best Cybersecurity Practices for Businesses
The Future of Cyber Security
How AI (Artificial Intelligence) will shape the future of Cyber Security Methodologies
Chapter Four: Analytics and Metrics for Big Data
Analytics and Metrics of Big Data and Data Science
Cybersecurity Analytics and Metrics
Conclusion
Bibliography