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Data science/ML/AI

Data science/ML/AI

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Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers πŸ‘‰ https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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Programming, data science, ML - free courses by Big Data SpecialistNetwork:Programming, data science, ML - free courses by Big Data SpecialistIndia31 607Technologies & Applications9 380

πŸ“ˆ Analytical overview of Telegram channel Data science/ML/AI

Channel Data science/ML/AI (@datascience_bds) in the English language segment is an active participant. Currently, the community unites 13 685 subscribers, ranking 9 380 in the Technologies & Applications category and 31 607 in the India region.

πŸ“Š Audience metrics and dynamics

Since its creation on Π½Π΅Π²Ρ–Π΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 13 685 subscribers.

According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 143 over the last 30 days and by 2 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 8.09%. Within the first 24 hours after publication, content typically collects 2.22% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 106 views. Within the first day, a publication typically gains 304 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 5.
  • Thematic interests: Content is focused on key topics such as panda, learning, row, api, ethic.

πŸ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
β€œData science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers πŸ‘‰ https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

Thanks to the high frequency of updates (latest data received on 11 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

13 685
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Posts Archive
Data science/ML/AI
Data science/ML/AI
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import_data.pdf1.35 KB

Data science/ML/AI
Data science/ML/AI
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Useful Python for data science cheat sheets

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Want to learn python programming like a pro. Checkout our channel @pyguru python where we provide πŸ”ΈFree Python content πŸ”ΈEbooks πŸ”ΈProgramming notes πŸ”ΈProjects πŸ”Έ& other resources including interview questions, exercises & Quizzes. Learn & Discuss with like minds, Join our channel now. https://t.me/+Covm5cVvIltkN2Vl https://t.me/+Covm5cVvIltkN2Vl https://t.me/+Covm5cVvIltkN2Vl

Data science/ML/AI
Data science/ML/AI
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Do you enjoy reading this channel? Perhaps you have thought about placing ads on it? To do this, follow three simple steps: 1) Sign up: https://telega.io/c/datascience_bds 2) Top up the balance in a convenient way 3) Create an advertising post If the topic of your post fits our channel, we will publish it with pleasure.

Data science/ML/AI
Data science/ML/AI
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Data Science and Machine Learning [PDF] Mathematical and Statistical Methods Dirk P. Kroese, Zdravko I. Botev, Thomas Taimre,
Data Science and Machine Learning [PDF] Mathematical and Statistical Methods Dirk P. Kroese, Zdravko I. Botev, Thomas Taimre, Radislav Vaisman 8th May 2022 533 pages πŸ”— Read online

Data science/ML/AI
Data science/ML/AI
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Repost from Programming, data science, ML - free courses by Big Data Specialist
Free Big Data Courses Complete Big Data 🎬 13 video lesson Duration ⏰: 2-3 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Class Central πŸ”— COURSE LINK Big Data 101 (Login Required) ⏳Modules: 6 Duration ⏰: 3 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: IBM via Cognitive Class πŸ”— COURSE LINK Introduction to Big Data - an overview of the 10 V's Rating⭐️: 4.4 out 5 Students πŸ‘¨β€πŸŽ“ :15,630 Duration ⏰ : 40min of on-demand video Teacher πŸ‘¨β€πŸ«: Taimur Zahid πŸ”— COURSE LINK MIT RES.LL-005 Mathematics of Big Data and Machine Learning, IAP 2020 🎬 20 video lesson Duration ⏰: 14 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: MIT open courseware πŸ”— Course Link NOC:Big Data Computing, IIT Patna 🎬 35 video lesson ⏰ 8 Modules Taught by: Dr. Rajiv Misra Source: NPTEL πŸ”— COURSE LINK Algorithms for Big Data (COMPSCI 229r) 🎬 25 video lesson Duration ⏰: 34 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Harvard University πŸ”— Course Link NOC:Algorithms for Big Data, IIT Madras 🎬 48 video lesson ⏰ 8 Modules Taught by: Prof. John Augustine Source: NPTEL πŸ”— COURSE LINK Big Data Hadoop Tutorial for Beginners 🎬 17 video lesson Duration ⏰: 4-5 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Great Learning πŸ”— Course Link Big Data Analytics Full Course In 10 Hours | Big Data Hadoop Tutorial 🎬 5 video lesson Duration ⏰: 10 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Great Learning πŸ”— Course Link Big Data Analytics ⏰ Free Online Course 🎬 70 video lesson Duration ⏰: 19 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: caltech via youtube πŸ”— Course Link Stanford Seminar - Big Data is (at least) Four Different Problems ⏰ Free Online Course 🎬 27 video lesson Duration ⏰: 1-2 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Stanford Online via YouTube πŸ”— Course Link #Big_Data βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Data science/ML/AI
Data science/ML/AI
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Repost from Programming, data science, ML - free courses by Big Data Specialist
Free Data Mining Courses NOC:Data Mining, IIT Kharagpur 🎬 44 video lesson ⏰ 8 Modules Taught by: Prof. Pabitra Mitra Source: NPTEL πŸ”— COURSE LINK Data Mining for Beginners | Data Mining Full course | Learn Data Mining in 10 Hours | Great Learning 🎬 17 video lesson Duration ⏰ : 10 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Great Learning πŸ”— COURSE LINK NOC:Business analytics and data mining Modeling using R, IIT Roorkee 🎬 56 video lesson ⏰ 12 Modules πŸ”— COURSE LINK NOC:Business Analytics & Data Mining Modeling Using R Part II, IIT Roorkee 🎬 20 video lesson ⏰ 4 Modules πŸ”— COURSE LINK Taught by: Dr. Gaurav Dixit Source: NPTEL Data Mining with Weka MOOC βœ… Free Online Course 🧱 5 modules 🎬 Video Lectures πŸƒβ€β™‚οΈ Self paced Source: University of Waikato Taught by: Ian H. Witten πŸ”— Course Link WEKA - Data Mining with Open Source Machine Learning Tool Rating⭐️: 4.2 out 5 Students πŸ‘¨β€πŸŽ“ : 12,485` Duration ⏰ : 3hr 30min of on-demand video Teacher πŸ‘¨β€πŸ«: DATAhill Solutions Srinivas Reddy πŸ”— COURSE LINK Data Mining Crash Course 🎬 6 video lesson Duration ⏰: 1-2 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Data Science Dojo πŸ”— Course Link Clustering in Data mining | K means Clustering Algorithm | Hierarchical Clustering | Great Learning 🎬 86 video lesson Duration ⏰: 3-4 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Great Learning πŸ”— Course Link Mining Online Data Across Social Networks ⏰ Free Online Course 🎬 30 video lesson Duration ⏰: 1-2 hours worth of material πŸƒβ€β™‚οΈ Self paced Source: Class Central πŸ”— Course Link DATA MINING (DM) ⏰ Free Online Course πŸƒβ€β™‚οΈ Self paced Source: YouTube πŸ”— Course Link #Data_Mining βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Data science/ML/AI
Data science/ML/AI
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Applications of Deep Neural Networks Washington University in St. Louis https://sites.wustl.edu/jeffheaton/t81-558/ βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Data science/ML/AI
Data science/ML/AI
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NOC: Reinforcement Learning, IIT Madras πŸ†“ Free Online Course πŸ’» 65 Lecture Videos ⏰ 12 Modules πŸƒβ€β™‚οΈ Self paced Teacher πŸ‘¨β€πŸ« : Dr. B. Ravindran πŸ”— https://nptel.ac.in/courses/106106143 #Reinforcement_Learning #IIT βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– πŸ‘‰Join @bigdataspecialist for moreπŸ‘ˆ

Data science/ML/AI
Data science/ML/AI
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Data science roadmap.

Data science/ML/AI
Data science/ML/AI
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Hey folks, this week's round of our programming quiz league is about data science. Here is the quiz link: http://t.me/QuizBot?start=H4Ow9sU8 Feel free to answer on those 8 short questions and let me know about your placement on final score. Also to those who celebrate today I wish Merry Christmas πŸŽ„πŸ₯³πŸ˜Š

Data science/ML/AI
Data science/ML/AI
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photo content

Data science/ML/AI
Data science/ML/AI
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DIVE INTO DEEP LEARNING ||d2l.ai Here's an Interactive deep learning book with code, math, and discussions. Implemented with PyTorch, NumPy/MXNet, and TensorFlow. Book Link : https://d2l.ai/ GitHub Repo: https://github.com/d2l-ai/d2l-en Stars: 15.7K Forks:3.4K #deep_learning #pyTorch #numPy #MXNet #TensorFlow #neural_networks βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more cool data science materials. *This channel belongs to @bigdataspecialist group

Data science/ML/AI
Data science/ML/AI
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Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estima
Often the hardest part of solving a machine learning problem can be finding the right estimator for the job. Different estimators are better suited for different types of data and different problems. The flowchart below is designed to give users a bit of a rough guide on how to approach problems with regard to which estimators to try on your data. Source: Scikit-learn

Data science/ML/AI
Data science/ML/AI
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Repost from Programming, data science, ML - free courses by Big Data Specialist
Graphic SQL reference for data manipulation Source: https://raw.githubusercontent.com/kelsfarmer/SQL/master/SQL%20Data%20Mani

Data science/ML/AI
Data science/ML/AI
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Data Science Projects.pdf2.96 KB

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photo content

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Data science/ML/AI
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127+ Data Science Projects with Python Code

Data science/ML/AI
Data science/ML/AI
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photo content

Data science/ML/AI
Data science/ML/AI
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DIMENSIONALITY REDUCTION Have you heard of Dimensionality ReductionπŸ‘€? If this is your first timeπŸ˜ƒ, then get your seats clos
DIMENSIONALITY REDUCTION Have you heard of Dimensionality ReductionπŸ‘€? If this is your first timeπŸ˜ƒ, then get your seats closerπŸ™‚. It means trimming down data to remove unwanted featuresπŸ‘Œ. Did this make any senseπŸ€·β€β™€οΈ? If it didn't then you must know that whenever you have a very large dataset, It can help you capture the majority of your dataset's information within a few number of features. Here's one methodπŸ˜ƒ of Dimensionality Reduction you must know. It's the Principal Component Analysis (PCA)😎. It gives us the ability to plot multivariate data🀯 in 2 dimensions and works perfectly☺️ in identifying the axis of greatest variance in our dataset. In this method, we take old sets of variables and convert them into a newer set. The new sets created are called principal components⭐️. There is a trade-off between reducing the number of variables while maintaining the accuracy of your modelπŸ‘πŸΌ. The next time you have problems working with very large datasets 🀯, you could try Dimensionality ReductionπŸ˜‰