Journaling - Readings, Muay Thai, Concepts and Articulations
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By Kevin von Duuglas-Ittu · Posted
What people don't really appreciate is that Nabil says he trained 13 months for this fight...and Superlek probably trained for two weeks. Good on Nabil, but the fight (and the promotion) just doesn't "mean" the same thing to each fighter, as much as there is enormous social media hype around these kinds of matchups. It's "entertainment" Muay Thai. In many ways it just isn't "real" for Thais (it lacks the social risks that gambled stadium fighting has). Fighting the stadium when Superlek was 18...that was REAL, because the social conditions of shame and pride and the cultural network of status struggle was infinitely at risk. One can't force it to be real. -
By Kevin von Duuglas-Ittu · Posted
I've been exploring ultrawides for a while, though basically drawn to them since I started shooting Muay Thai though I didn't know how to use them. There was always the sense that I wanted to weave together very different focal lengths. Since shooting with the Contax which I really love, on a bigger sensor format I've been drawn further in. So here is an experiment, using keyframes, big contrast video and telephoto images, to capture the mood and energy of a training session with Chatchai. This is was just a sketch from a single very quick shoot (I think 3 very short videos, maybe 100 still frames shot), maybe 5 minutes of photography altogether. I wanted it to be very bare bones to see if I could whip up an energy and feeling that I could maybe use on a larger project. The short is much aided by the music by Anand who I'm working with on a big, experimental writing project. wh -
By Gurpreet555 · Posted
Exactness and review are two essential measurements utilized in assessing the execution of machine learning models, especially in classification errands. Both are vital in understanding how well a demonstrate performs in recognizing between pertinent and unimportant comes about, but they center on diverse viewpoints of accuracy. Data Science Course in Pune Precision measures the precision of positive forecasts made by a show. It is calculated as the number of genuine positive comes about partitioned by the add up to number of positive forecasts (genuine positives furthermore wrong positives). In other words, exactness answers the address: "Out of all the occurrences the demonstrate labeled as positive, how numerous were really redress?" A tall accuracy score demonstrates that when the show predicts a positive result, it is ordinarily redress. This metric is especially imperative in scenarios where wrong positives carry critical results, such as in spam location. If an mail channel marks a authentic e-mail as spam, it may result in critical messages being missed. On the other hand, review, too known as affectability, centers on the model’s capacity to distinguish all pertinent occurrences. It is calculated as the number of genuine positives separated by the whole of genuine positives and untrue negatives. This implies review answers the address: "Out of all genuine positive cases, how numerous did the demonstrate accurately recognize?" A tall review score recommends that the show does not miss numerous important occurrences, which is especially valuable in restorative analyze. For illustration, in cancer discovery, a tall review guarantees that about all cancerous cases are distinguished, indeed if it implies a few untrue positives are included. The trade-off between exactness and review is a common challenge in machine learning. A show can be balanced to favor one over the other depending on the application. Expanding accuracy regularly comes at the fetched of review, as the show gets to be more preservationist in making positive forecasts. Then again, expanding review might lower accuracy, as the demonstrate gets to be more indulgent in labeling occasions as positive. The adjust between the two is regularly spoken to utilizing the F1-score, which is the consonant cruel of exactness and recall. In down to earth applications, the choice between prioritizing accuracy or review depends on the particular needs of the assignment. In extortion discovery, for occurrence, tall exactness is vital to maintain a strategic distance from dishonestly denouncing authentic exchanges. In differentiate, tall review is basic in look motors to guarantee all pertinent comes about are recovered. Understanding the contrast between these two measurements makes a difference information researchers fine-tune models for ideal execution based on their targets.
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