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Codehub (@pythonadvisorai) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 31 526 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 4 219-o'rinni va Malayziya mintaqasida 1 037-o'rinni egallagan.

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невідомо sanasidan buyon loyiha tez o‘sib, 31 526 obunachiga ega bo‘ldi.

28 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -428 ga, so‘nggi 24 soatda esa -8 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 7.54% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
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Yuqori yangilanish chastotasi (oxirgi ma’lumot 29 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

31 526
Obunachilar
-824 soatlar
-927 kun
-42830 kun
Postlar arxiv
Codehub
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Codehub
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Algorithm Name PCA/T-SNE Description Mostly used to decrease the dimensionality of the data. The algorithms reduce the number of features to 3 or 4 vectors with the highest variances Type Dimension Reduction

Codehub
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Algorithm Name Recommender system Description Help to define the relevant data for making a recommendation. Type Clustering

Codehub
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Algorithm Name Hierarchical clustering Description Splits clusters along a hierarchical tree to form a classification system. Can be used for Cluster loyalty-card customer Type Clustering

Codehub
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Algorithm Name Gaussian mixture model Description A generalization of k-means clustering that provides more flexibility in the size and shape of groups (clusters) Type Clustering

Codehub
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Algorithm Name K-means clustering Description Puts data into some groups (k) that each contains data with similar characteristics (as determined by the model, not in advance by humans) Type Clustering

Codehub
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Unsupervised learning In unsupervised learning, an algorithm explores input data without being given an explicit output variable (e.g., explores customer demographic data to identify patterns) You can use it when you do not know how to classify the data, and you want the algorithm to find patterns and classify the data for you

Codehub
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Algorithm Gradient-boosting trees Description Gradient-boosting trees is a state-of-the-art classification/regression technique. It is focusing on the error committed by the previous trees and tries to correct it. Type Regression Classification

Codehub
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Algorithm AdaBoost Description Classification or regression technique that uses a multitude of models to come up with a decision but weighs them based on their accuracy in predicting the outcome Type Regression Classification

Codehub
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Algorithm Random forest Description The algorithm is built upon a decision tree to improve the accuracy drastically. Random forest generates many times simple decision trees and uses the ‘majority vote’ method to decide on which label to return. For the classification task, the final prediction will be the one with the most vote; while for the regression task, the average prediction of all the trees is the final prediction. Type Regression Classification

Codehub
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Algorithm Support vector machine Description Support Vector Machine, or SVM, is typically used for the classification task. SVM algorithm finds a hyperplane that optimally divided the classes. It is best used with a non-linear solver. Type Regression (not very common) Classification

Codehub
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Algorithm Naive Bayes Description The Bayesian method is a classification method that makes use of the Bayesian theorem. The theorem updates the prior knowledge of an event with the independent probability of each feature that can affect the event. Type Regression Classification

Codehub
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Algorithm Decision tree Description Highly interpretable classification or regression model that splits data-feature values into branches at decision nodes (e.g., if a feature is a color, each possible color becomes a new branch) until a final decision output is made Type Regression Classification

Codehub
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Algorithm Logistic regression Description Extension of linear regression that’s used for classification tasks. The output variable 3is binary (e.g., only black or white) rather than continuous (e.g., an infinite list of potential colors) Type Classification

Codehub
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Algorithm Linear regression Description Finds a way to correlate each feature to the output to help predict future values. Type Regression

Codehub
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Codehub
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👆DevBytes is just the right app for professional and enthusiast programmers to stay in touch with all the latest updates, ti
👆DevBytes is just the right app for professional and enthusiast programmers to stay in touch with all the latest updates, tips, tricks and jobs. It gives all programming news in less than 64 words and also has sharable code snippets for your reference. App link :https://bit.ly/3SYjcNW Download now !! 🔥

Codehub
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Codehub
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learn build your own game using python🥰👨‍💻 - https://inprogrammer.com/web-stories/learn-build-your-own-game-using-python/

Codehub
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Python basic for beginners🥰