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Why The Subtle Art of Not Giving a F*ck Still Resonates
Why Less Caring Can Lead to a Better Life: Mark Manson’s Brutally Honest Case for Better Values, Clearer Priorities, and Meaningful Struggle Most self-help books promise a better life through more confidence, more optimism, and more success. Mark Manson’s The Subtle Art of Not Giving a F*ck goes in the opposite direction. First published in… Continue reading
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How Alex Hormozi Turned Irresistible Value Into an Empire—And How You Can Too
Hey, so I just finished going through Alex Hormozi’s $100M Offers, and I wanted to break it down for you like I’d explain it to a friend—no jargon, just real talk for solopreneurs like us trying to build something big. The Big Idea: Don’t Just Sell Services—Make Irresistible Offers Here’s the gist: Hormozi says most… Continue reading
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The Three Lanes to Wealth: Sidewalk, Slowlane, Fastlane
A practical, entrepreneur-style breakdown of DeMarco’s Fastlane mindset, the 3 wealth paths, and the CENTS checklist for building scalable wealth. 1) Sidewalk (the “consume now” lane) What I took away here is that the Sidewalk isn’t just “poor people behavior.” It’s a pattern: DeMarco uses this lane as a warning: if you don’t build systems… Continue reading
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What I took from Feel-Good Productivity (Ali Abdaal)
How I’m using Play, Clarity, and Recovery to get more done at work—without burning out So the big idea of the book is pretty simple, but it kind of flips the usual productivity story. Most of us assume: work hard → achieve more → then feel good.Ali’s point is: it’s usually the other way round.… Continue reading
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Visualizing Linear Regression and Gradient Descent
Overview In this lecture we build intuition for how optimizes a model. We coordinate three visualizations: 1. Training Data and Regression Lines We simulate a realistic training set of 30 points (size in square feet vs. price in $1000s. The red points are the observed data. The colored lines show five successive fits produced by… Continue reading
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Linear Regression and Gradient Descent
Linear Regression Model In a simple linear regression problem, our goal is to fit a straight line to data points that best predicts the output from an input . The model is expressed as: The objective of linear regression is to find parameters and that make as close as possible to the actual values in… Continue reading
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Understanding the Learning Rate in Gradient Descent
Key Idea: The learning rate controls how large a step the gradient descent algorithm takes in each iteration when moving toward the minimum of a cost function. Choosing appropriately is crucial: too small leads to painfully slow learning, while too large can cause divergence or oscillation. 1. The Gradient Descent Rule Gradient descent is an… Continue reading
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Gradient Descent Intuition
Gradient Descent Update Rules Repeat until convergence: Here: Simplified Case: Single Variable To build intuition, consider a simplified cost function depending only on . The gradient descent update becomes: Our goal is to find the value of that minimizes . Visualizing the Process Imagine a graph where: The graph of is U-shaped, indicating a convex… Continue reading
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Gradient Descent
Introduction Gradient descent is one of the most widely used optimization algorithms in machine learning.It provides a simple way to minimize a cost function by iteratively adjusting parameters in the direction of steepest descent. The Update Rule At each iteration, the parameters are updated using the following rule: Here: Key Concepts 1. Assignment vs. Equality… Continue reading
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Computing the Cost Function with Python
For linear regression with one variable, the cost function is defined as: where – : the model’s prediction for example given parameters and . – : the squared error between the prediction and the true target value. – The sum adds these squared errors over all training examples. – Dividing by gives the average squared… Continue reading
About Me
My name is Cenk, and I am an economist. I write on this internet site on economics, econometrics, finance, value-investing, programming, calculus, basketball, history, foods, books, self-improvement, well-being and productivity. This internet site is a personal blog, and the posts reflect my personal views and do not represent where I have been working.
For my academic works, please visit this site: https://cenkufukyildiran.academia.edu/
Posts related to financial markets, trading, investing and similar posts are not for financial advice purposes.