Notes, summaries, assignments, exams, and problems

Historical Source Evaluation

Understanding Historical Source Evaluation

Timeline of Key Events (American & French Revolutions)

• American War of Independence: 1775 - 1783 (French involvement)
• Assembly of Notables: 22 Feb - 25 May 1787
• Lit De Justice: 6 Aug 1787, 8 May 1788
• Day of Tiles: 10 June 1788
• Harvest Crisis: 1788
• Pamphlet War: 1788-1789
• Cahiers De Doléances: 1789 (List of grievances)
• Rural Revolt: March 1789
• Réveillon Riots: 27-28 April 1789
• Estates-General: May 1789
• Declaration of the National Assembly: 17 June 1789
• Tennis Court Oath: 20 June 1789
• Royal Session: 23 June 1789
• Necker’s Dismissal: 11 July 1789
• Fall of the Bastille: 14 July 1789
• Municipal Revolutions: 13-17 July 1789
• The Great Fear: 20 July - 6 Aug 1789
• Night of 4 August: Abolition of

Heuristic Functions in AI

A heuristic function is a function used in algorithms, especially in search and optimization problems, to estimate the cost or value of a particular state or action. It provides an informed guess to guide decision-making towards an optimal or near-optimal solution efficiently.

Key Aspects of a Heuristic Function

• Estimation, Not Exact: It provides an approximate cost to reach the goal from a given state.
• Improves Efficiency: Helps reduce the number of states explored, speeding up search algorithms.
• Domain-Specific: Often designed based on the specific problem being solved.

The A* Algorithm Explained

A* (A-star) is one of the most popular and widely used pathfinding and graph traversal algorithms. It is commonly used in artificial... Continue reading "Artificial Intelligence Fundamentals: Algorithms, Agents, and Applications" »

Statistical Measures and Causal Inference Concepts

Measures of Dispersion and Relationship

Variance

Variance: Estimates how far a set of numbers (random) are spread out from their mean value.

Covariance

Covariance: The relationship between two variables.

• Cov = 0: Unsure of the relationship.
• Cov > 0: Suggests Y will be above average when X is above average.
• Cov < 0: Suggests Y will be below average when X is above average.

The formula for variance is often expressed as: $\mathbb{E}[X^2] - (\mathbb{E}[X])^2$ (where $\mathbb{E}$ is the Expected Value).

The formula for covariance between two variables $X$ and $Y$ is: $\mathbb{E}[(X - \mathbb{E}[X])(Y - \mathbb{E}[Y])]$

Pearson's Correlation Coefficient

Standardizes covariance between -1 and 1:

Pearson’s

Lecture 1: Moore's Law

Moore's Law: The number of transistors on microchips doubles every two years.

Lecture 2: Logic Gates

AND, OR, and NOT gates are universal.

Logic word problem steps:

Example: In a bank, there were four employees: the bank manager, assistant manager, teller, and the security guard. The bank has a single vault for the storage of their money. This vault was designed so that it needs four signals to open it. These four signals are from the bank manager, assistant manager, teller, and the security guard. For the vault to open, it needs the following conditions:

1. No single employee can open the vault.
2. It can be opened with three employees as long as one of them is the manager.
3. It can be opened by the manager together with the assistant

Essential Statistical & Numerical Concepts

This document covers fundamental questions and answers across various topics in statistics, numerical methods, and data analysis. Each section provides a concise explanation of key concepts.

1. What is Interpolation?

Interpolation is a mathematical technique used to estimate unknown values that fall between known data points. It involves creating a function or model based on the given data and using it to predict values within the range of the data, rather than extrapolating outside it. This method is commonly applied in fields like data analysis, engineering, and computer graphics for filling in missing data or smoothing curves.

2. Regula Falsi Method Formula for Finding Roots

The formula for finding... Continue reading "Core Concepts in Statistics and Numerical Analysis" »

Understanding Ancient Mesoamerican Civilizations

Delve into the rich history and complex structures of ancient Mesoamerican societies. This document highlights key aspects, from their societal organization and agricultural innovations to their lasting cultural and historical impact.

Key Aspects of Mesoamerican Societies

• Classic Period Decline: Societal Shifts

  An understanding of the societal, political, and economic shifts following the Classic period is crucial to grasp its consequences.

• Monumental Architecture and Social Hierarchy

  Analyzing how the construction of large-scale structures reveals the power structures and social hierarchies within Mesoamerican societies.

• Mesoamerican Calendars: Culture and Daily Life

  Explaining the importance of the

Software Engineering and Processes

Agile Manifesto

• Individuals/Interactions over Processes
• Working software over documentation
• Collaboration over negotiation
• Responding to change over following a plan

Requirements Engineering

Descriptions of the services that a system should provide and the constraints on its operation.

Functional

What the system should do.

Non-functional

Not directly concerned with the specific services delivered by the system to its users.

Quality Attributes

A scenario describing quality attributes typically involves these elements:

1. Source: Origin of the stimulus.
2. Stimulus: The event arriving.
3. Artifact: Where the event arrives.
4. Environment: Conditions in which the scenario takes place.
5. Response: The result of the event.
6. Response Measure: Must

Sustainable Development Goals (SDGs)

Purpose of Sustainable Development

1. Reduce inequalities.
2. Caring for the environment.
3. Promote collaboration between social agents (productive agents).

Five Dimensions of the SDGs

The SDGs are "unique and special" in at least five dimensions:

1. All countries participate.
2. Target three dimensions: environmental, economic, and social.
3. All kinds of partners are involved.
4. Institutionally integrated.
5. More visible in public discourse.

Key Sustainability Metrics for Profitability

• Energy Efficiency and Cost Reduction
• Waste Reduction
• Water Efficiency
• Supply Chain Sustainability
• Brand Reputation
• Regulatory Compliance
• Productivity and Employee Engagement
• Innovation and New Product Development
• Carbon Footprint Reduction
• Return on Investment (ROI)

Chapter 1: Understanding Variables

Types of Variables

• Categorical: Smoker (current, former, no)
• Ordinal: Non, light, moderate, heavy smoker (ordered categories)
• Quantitative: BMI, Age, Weight (numerical measurements)

Key Definitions

• Observation: Measurements are made (individual or aggregate).
• Variable: The generic characteristic we measure (e.g., age).
• Value: A realized measurement (e.g., 27).

Chapter 2: Statistical Studies

Surveys: Census and Sampling

• Goal: Describe population characteristics.
• Census: Attempts to reach the entire population (costly, time-consuming).
• Sampling: Uses a sample of the population (allows for inferences, saves time and money).
• Simple Random Sampling: Based on probability.
• Issues with Sampling: Under-coverage, volunteer bias,