Morgan

@brawnvivant.bsky.social

652 Followers 288 Following

Tech bro test results: "You scored 11%. That puts you in the not a tech bro range."
Dead golfer boss Lew Hayward from the movie Scrooged (1988) looking like shit
Given Trump's statements while campaigning for President, none of this should be surprising. What is astonishing is that even the playbook that most Americans believed was President Trump’s roadmap—Project 2025—underestimated the stampede. We can now say, with some confidence, that Project 2025 represents a more moderate and gradual dismantling of “inside the beltway” customs compared to the President’s actual intentions.
What the fuck
McDonald's bun ingredients: Enriched Flour (wheat Flour, Malted Barley Flour, Niacin, Reduced Iron, Thiamine Mononitrate, Riboflavin, Folic Acid), Water, Sugar, Yeast, Soybean Oil, Contains 2% Or Less: Salt, Dextrose, Corn Starch, Modified Food Starch, Wheat Gluten, Vinegar, Vegetable Proteins (pea, Potato, Rice And/or Faba), Sunflower And/or Canola Oil, Maltodextrin, Natural Flavors, Dough Conditioners (enzymes, Ascorbic Acid, Monoglycerides).
Two black cats in different spots on a couch
Screenshot of a conversation with Claude: Returning to deep learning and LLMs, I saw some recommendations for Mathematics for Machine Learning by Deisenroth, Faisal, and Ong as a good overview of the relevant math. I decided to pick up that, Introduction to Statistical Learning with Python, and the newer book Deep Learning: Foundations and Concepts by Bishop. What do you think about that as a starting point? What will I be missing? Edit That's an excellent and well-balanced selection! You've chosen three books that complement each other very well and will give you a strong foundation. Let me break down what each contributes and what gaps might remain: Your Selected Books - Strengths Mathematics for Machine Learning (Deisenroth, Faisal, Ong) Excellent bridge between pure math and ML applications Covers linear algebra, calculus, and probability with ML context More focused and practical than pure math texts Free online version available Introduction to Statistical Learning with Python (James, Witten, Hastie, Tibshirani) Perfect practical introduction to ML concepts Excellent balance of theory and hands-on coding Strong statistical foundation (the Python version is newer and excellent) Less intimidating than Elements of Statistical Learning while still rigorous Deep Learning: Foundations and Concepts (Bishop, 2024) This is Bishop's new book, likely more accessible than his classic PRML Should provide modern treatment of deep learning with solid mathematical grounding Bishop is excellent at mathematical exposition
I'd be happy to explain what this economic report means. This is information about the Institute for Supply Management (ISM) Manufacturing Index for April 2025, which is an important economic indicator. Here's what the different parts mean: "ISM not as weak as feared" - The overall manufacturing index came in at 48.7, which was better than economists' expectations of 47.9, though still below 50 (which is the dividing line between expansion and contraction). "Prices lower than expected" - The prices component of the report showed lower inflation in manufacturing than analysts anticipated, which is generally positive news for inflation concerns. "New orders and employment higher than expected but both of those are in contraction" - While these components beat expectations, they're still below 50, indicating that both new orders and manufacturing employment are contracting, just not as severely as economists predicted. "US APRIL ISM MANUFACTURING INDEX FALLS TO 48.7; EST. 47.9" - This confirms the headline number - manufacturing activity is contracting (below 50) but not as badly as expected. "US ISM FACTORY PRODUCTION GAUGE DROPS TO LOWEST SINCE MAY 2020" - This is more concerning - it indicates that actual factory output has fallen to levels not seen since the early COVID pandemic period, suggesting significant weakness in manufacturing production. In summary, this report shows the manufacturing sector is still contracting, but slightly better than economists expected. The most worrying part is the factory production component hitting a nearly 5-year low, which points to significant weakness in actual manufacturing output. This mixed economic data is important for understanding the current state of the US economy and potential future Federal Reserve actions.