Value at Risk (VaR) provides a single number that summarizes the total financial risk in a portfolio or an asset. It was pioneered by J.P. Morgan in 1990 and has become widely used by fund managers, corporate management as well as financial institutions. This metric was also chosen by the regulators to set capital requirements for market risk, credit risk and operational risk. In summary, VaR is for managing, as well as measuring risk. [1]

VaR is defined as the worst loss expected from holding a portfolio or an asset over a given period of time with a confidence level…

In Q-Learning, we represent the Q-value as a table. However, in many real-world problems, there are enormous state and/or action spaces and tabular representation is insufficient. For instance, Computer Go has 10¹⁷⁰ states and games like Mario Bro has continuous state space. When it is impossible to store all possible combinations of state and action pair values in the 2-D array or Q table, we need to use Deep Q-Network (DQN) instead of Q-Learning algorithm. [1]

DQN is also a model-free RL algorithm where the modern deep learning technique is used. DQN algorithms use Q-learning to learn the best action…

Sudoku is a popular Japanese puzzle game that is based on the logical placement of numbers. It doesn’t require any special mathematics skills or calculations. Let’s look at an example below from Wikipedia:

Sudoku is a popular Japanese puzzle game that is based on the logical placement of numbers. It doesn’t require any special mathematics skills or calculations. Let’s look at an example below from Wikipedia:

Reinforcement Learning (RL) is one of the learning paradigms in machine learning that learns an optimal policy mapping states to actions by interacting with an environment to achieve the goal. In this article, I will introduce the two most commonly used RL algorithm: Q-Learning and SARSA.

Similar to the Monte Carlo Algorithm (MC), Q-Learning and SARSA algorithms are also **model-free RL algorithms** that **do not use the transition probability distribution** associated with Markov Decision Process (MDP). Instead, they **learn** the optimal policy **from experience**. The main difference between MC and Q-Learning or SARSA algorithm is that **MC needs to sample…**

Machine Translation plays a vital role in today’s digitized and globalized world. It benefits society by processing and translating one natural language into some other natural language. With advances in technology, there is an enormous amount of information being exchanged between different regions with different languages. This boosts the demand for Machine Translation to grow exponentially over the last few decades. Owing to that, Machine Translation has become an active research area over the past couple of years. It can be divided into three distinct approaches: rule-based approaches, statistical approaches, and neural approaches. …

Recall the Agent-Environment Interface introduced in Part 1, the observation is the perception of the environment for the agent, the action will change the environment’s state, the reward is a scalar value that indicates how well the agent is doing at step t and the agent’s objective is to maximize the cumulative reward.

In previous articles, I have discussed how to perform one-sample hypothesis tests and two-sample hypothesis test. So, what if we would like to compare several population means? In this article, I will introduce an analysis of variance (ANOVA) which involves comparing multiple unknown μ’s.

It is a test where a particular factor has more than 2 groups or levels of interest. For example, let μ be the true mean annual salary of graduates

Single-factor of interest = Study subjects

Assume we have 6 categories of study subjects, `Factor levels = athematics and Statistics, Economics and Finance, Environmental Sciences, Political Science, Social…`

A Hypothesis Test is a statistical test that is used to test the assumption or hypothesis made and draw a conclusion about the entire population. In the previous article, I have introduced how to do one-sample hypothesis tests under different situations. In this article, I will share how hypothesis tests can extend to comparing samples from 2 populations instead of one.

The **FIVE steps process of hypothesis testing** is the same as one-sample hypothesis tests except for the calculation of test statistics, in summary:

- Define the Null Hypothesis (H₀)
- Define the Alternative Hypothesis (H₁)
- Set the Level of Significance (α)
- …

In this article, I will introduce the fundamental of the chi-square test (χ2), a statistical method to make the inference about the distribution of a variable or to decide whether there is a relationship exists between two variables of a population. The inference relies on the χ2 distribution curve, dependent upon the number of degrees of freedom d.f.

Data Analyst | MSc. Artificial Intelligence | LinkedIn — https://www.linkedin.com/in/thet-thet-yee-deyu/