In the quest for increased productivity, it's easy to fall into the trap of consuming countless articles and videos when you should begin working on the tasks. However, the true path to productivity lies in understanding the underlying reasons for unproductivity and developing personalised strategies to overcome them.
I recently stumbled upon an insightful video on YouTube titled How to Get Good at Small Talk, and Even Enjoy It - YouTube The video highlights several key points about the importance of small talk in our daily lives: 1. Small talk is more than just chit-chat; it is a
How humans work with AI will be one of the most critical topics in our generation. In light of this, I use different generative AI platforms to survey human opinions based on books, words from thought leaders and government policies. Books Based on our discussion and the information provided from
The author of Reinforcement Learning: An Introduction gives an example of a state-value function using a grid (Example 3.5). Readers like me may be confused about how the values of each cell are calculated. The author provided codes to compute the state value. The codes are written in LISP.
Reading is a beacon of knowledge in the lifelong learning journey, offering pathways to myriad destinations. Yet, as I reflect on my reading habits, I've come to recognise the existence of distinct reading methodologies, each serving a unique purpose in the quest for understanding. 1. The Quest for
Recently, I have been reading Reinforcement Learning: An Introduction by Sutton and Barto. In Chapter 3, Session 5, I found the derivation of the Bellman Equation hard to follow. I hope this supplementary note can provide information to the coming students. The section contains all the necessary information to understand
![[Write to Learn] How Exploring Can Increase Long-Term Reward? An Illustration Using Epsilon-Greedy Method.](/content/images/size/w600/2024/03/48187dc35a15c033986c222bb7028a66.jpg)
The example presented in Reinforcement Learning: An Introduction by Sutton and Barto. A possible value added by this article is to provide a more detailed explanation and code snippets to replicate the example. The 10-armed Bandit Example For readers not familiar with the k-armed bandit problem, you are repeatedly faced
TLDR For two groups with a two-sided alternative, normal distribution with homogeneous variances ( \(\sigma_0^2 = \sigma_1 ^2 = \sigma ^2)\) and equal sample sizes (\(n_0 = n_1 = n\)), \[n = \frac{16}{\Delta^2}\] where \[\Delta = \frac{\mu_0 - \mu_1}{\sigma} = \frac{\delta}{\sigma}\] Examples: What sample
Hello Brilliant Minds and Passionate Creators, Welcome to this week’s edition of our journey together in the fascinating world of "Building in Public." Each step we take is a story of discovery, learning, and sharing, aimed at not just building projects but fostering a vibrant community of
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I wouldn't say I liked geography in secondary school. It seemed disconnected from the real world – all about memorising facts and theories. It wasn't until I read 'Guns, Germs, and Steel' that I grasped geography's profound influence on cultures and economies. From
1. Fundamentals 1. The Art and Science of Decision-Making 2. Fundamentals of Interest and Loan 2. Key Objective and Its Components 1. The Balance Between Risk and Reward 2. Commonly Used Risk Metrics 3. Prediction into the Future 1. Estimating Long-term Impact from Short-term Outcome 2. Creating Models of the
This week, I compared the difference between the Potential Outcome Model (Rubin Casual Model) and Structural Causal Model frameworks for causal inference. I failed to grasp the difference between the two. Still, I can share some resources on this matter. While I believe the comparison has more of a theoretical