uz
Feedback
Data Science & Machine Learning

Data Science & Machine Learning

Kanalga Telegram’da o‘tish

Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

Ko'proq ko'rsatish

📈 Telegram kanali Data Science & Machine Learning analitikasi

Data Science & Machine Learning (@datasciencefun) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 75 943 obunachidan iborat bo'lib, Taʼlim toifasida 2 090-o'rinni va Hindiston mintaqasida 4 174-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 75 943 obunachiga ega bo‘ldi.

24 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 774 ga, so‘nggi 24 soatda esa 73 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 2.93% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 0.73% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 223 marta ko‘riladi; birinchi sutkada odatda 552 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 3 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent learning, accuracy, distribution, panda, dataset kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data

Yuqori yangilanish chastotasi (oxirgi ma’lumot 25 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

75 943
Obunachilar
+7324 soatlar
+1297 kunlar
+77430 kunlar
Postlar arxiv
Which Scipy package can be used to solve differential equations?
Anonymous voting

Which Scipy package can be used for standard continuous and discrete probability distributions?
Anonymous voting

Keyboard shortcuts for data scientists

Which of the following is not a function of scikit learn?
Anonymous voting

An Artificial Neuron Network (ANN), popularly known as Neural Network is a computational model based on the structure and functions of biological neural networks. It is like an artificial human nervous system for receiving, processing, and transmitting information in terms of Computer Science. Basically, there are 3 different layers in a neural network : Input Layer (All the inputs are fed in the model through this layer) Hidden Layers (There can be more than one hidden layers which are used for processing the inputs received from the input layers) Output Layer (The data after processing is made available at the output layer) Graph data can be used with a lot of learning tasks contain a lot rich relation data among elements. For example, modeling physics system, predicting protein interface, and classifying diseases require that a model learns from graph inputs. Graph reasoning models can also be used for learning from non-structural data like texts and images and reasoning on extracted structures.

Free Resources for Hacking and Programming 👇👇 https://t.me/joinchat/ZYXe60w7YisyNWEx

Top Bayesian Algorithms and Methods: - Naive Bayes. - Averages one-dependence estimators. - Bayesian belief networks. - Gaussian naive Bayes. - Multinomial naive Bayes. - Bayesian networks.

SQL-cheat-sheet.pdf2.25 KB

SQL Cheetsheet

Data science Bootcamp with 5 projects 👇👇 https://www.udemy.com/course/data-science-bootcamp-with-python/?couponCode=FREE_UDS [Free for limited time]

Hello, guys! Spring Boot Framework's news, articles and courses with daily updates. #springboot #springframework #java Perfect way learn new stuff every day and always be up-to-date 💪 No ads ⛔ Join the channel 👇👇👇👇👇 https://t.me/SpringFrameworkZone

photo content

Data Analysis Real world use-cases- Hands on Python 👇👇 https://www.udemy.com/course/data-analysis-real-world-use-cases-hands-on-python/?couponCode=MOTHERS_DAY [Free for limited time only]

Hello, guys! Download Programming ebooks for FREE. All books from 2016 year. Join the channel: https://t.me/progerbooks

Complete 2020 Data Science & Machine Learning Bootcamp 👇👇 https://t.me/joinchat/ZYXe60w7YisyNWEx

Top 10 Computer Vision Project Ideas 1. Edge Detection 2. Photo Sketching 3. Detecting Contours 4. Collage Mosaic Generator 5. Barcode and QR Code Scanner 6. Face Detection 7. Blur the Face 8. Image Segmentation 9. Human Counting with OpenCV 10. Colour Detection