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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 SpecialistIndia28 863Technologies & Applications8 914

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 13 906 subscribers, ranking 8 914 in the Technologies & Applications category and 28 863 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 13 906 subscribers.

According to the latest data from 29 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 86 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 7.48%. Within the first 24 hours after publication, content typically collects 2.04% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 1 039 views. Within the first day, a publication typically gains 284 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 30 August, 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.

13 906
Subscribers
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Posts Archive
Data science/ML/AI
Data science/ML/AI
13 906
Repost from Python Learning
Netflix ML Architecture
Netflix ML Architecture

Data science/ML/AI
Data science/ML/AI
13 906
Finding your career path in Data
Finding your career path in Data

Data science/ML/AI
Data science/ML/AI
13 906
Data Analysis Masterclass Using Spreadsheet, MS excel and Tableau This is a Condensed course that will teach you all you need to know about how to get started and get going with data analysis we will start with learning how to use Excel and spreadsheet then use Tableau for Data analysis. This course is made for anyone who wants to learn the art of Data analysis and data visualization. We will begin by learning how to use Excel and Spreadsheet then we will learn the various steps for doing data analysis which are data cleaning, preparation and finally data visualization after which we will use all of these learned skills to create a real interaction dashboard for our projects in Tableau. This course should prepare you to utilize Excel, Spreadsheet and Tableau to do your next analysis with confidence. You will be able to proudly showcase your skills to the world and add it to your resume. πŸ†“ Free Online Course 🎬 video lessons πŸƒβ€β™‚οΈ Self paced Modules ⏰: 4 Source: Skill Share πŸ”— Course Link #Data_Analysis #Excel #Tableau 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
13 906
Data Scientist, Data Engineer and Data Analyst
Data Scientist, Data Engineer and Data Analyst

Data science/ML/AI
Data science/ML/AI
13 906
Accelerating Deep Learning with GPUs (Login Required) Training complex deep learning models with large datasets takes along time. In this course, you will learn how to use accelerated GPU hardware to overcome the scalability problem in deep learning. You can use accelerated hardware such as Google’s Tensor Processing Unit (TPU) or Nvidia GPU to accelerate your convolutional neural network computations time on the Cloud. These chips are specifically designed to support the training of neural networks, as well as the use of trained networks (inference). Accelerated hardware has recently been proven to significantly reduce training time. πŸ†“ Free Online Course Rating⭐️: 4.7 out 5 🎬 video lesson πŸƒβ€β™‚οΈ Self paced Duration ⏰: More than 7 hours worth of material Source: cognitiveclass πŸ”— Course Link #deep_Learning 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
13 906
Data Science vs AI vs ML
Data Science vs AI vs ML

Data science/ML/AI
Data science/ML/AI
13 906
Deep Learning Notes

Data science/ML/AI
Data science/ML/AI
13 906
Introduction to the Data Science Process
Introduction to the Data Science Process

Data science/ML/AI
Data science/ML/AI
13 906
Data Science Ethics (Login Required) Utilize the framework provided in the course to analyze concerns related to data science ethics. Explore the broader impact of the data science field on modern society and the principles of fairness, accountability and transparency. Examine the need for voluntary disclosure when leveraging metadata to inform basic algorithms and/or complex artificial intelligence systems. Learn best practices for responsible data management. Gain an understanding of the significance of the Fair Information Practices Principles Act and the laws concerning the "right to be forgotten." 🎬 video lessons Rating⭐️: 4.1 out 5 πŸƒβ€β™‚οΈ Self paced Source: University of Michigan πŸ”— Course Link #data_science 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
13 906
Amazon Data Scientist Interview Process
Amazon Data Scientist Interview Process

Data science/ML/AI
Data science/ML/AI
13 906
MIT 6.S191: Introduction to Deep Learning 2021 Created by MIT ⏰ 29 hours worth of material 🎬 43 Video lessons πŸ‘¨β€πŸ« Teacher: Alexander Amini πŸ”— Course link #deeplearning #ai #MIT 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
13 906
Your Guide to Latent Dirichlet Allocation Latent Dirichlet Allocation (LDA) is a β€œgenerative probabilistic model” of a collec
Your Guide to Latent Dirichlet Allocation Latent Dirichlet Allocation (LDA) is a β€œgenerative probabilistic model” of a collection of composites made up of parts. Its uses include Natural Language Processing (NLP) and topic modelling, among others. In terms of topic modelling, the composites are documents and the parts are words and/or phrases (phrases n words in length are referred to as n-grams). But you could apply LDA to DNA and nucleotides, pizzas and toppings, molecules and atoms, employees and skills, or keyboards and crumbs. The probabilistic topic model estimated by LDA consists of two tables (matrices). The first table describes the probability or chance of selecting a particular part when sampling a particular topic (category). Link #ml #data_science 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
13 906
Foundations of Data Science by Avrim Blum, John Hopcroft, and Ravindran Kannan πŸ“„ 479 pages #data_science #foundations_of_data_Science βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž– Join @datascience_bds for more

Data science/ML/AI
Data science/ML/AI
13 906
Data Science with other fields of science
Data Science with other fields of science

Data science/ML/AI
Data science/ML/AI
13 906
Big and Sparse Data Sciences Integration with Theory, Experiment, Simulations, and Uncertainty Quantification
Big and Sparse Data Sciences Integration with Theory, Experiment, Simulations, and Uncertainty Quantification

Data science/ML/AI
Data science/ML/AI
13 906
100 Days of Data Science Challenge
100 Days of Data Science Challenge

Data science/ML/AI
Data science/ML/AI
13 906
Why choose data science
Why choose data science

Data science/ML/AI
Data science/ML/AI
13 906
photo content

Data science/ML/AI
Data science/ML/AI
13 906
Data Science for Engineers, IIT Madras πŸ†“ Free Online Course πŸ’» 50 Lecture Videos ⏰ 8 Module πŸƒβ€β™‚οΈ Self paced Teacher πŸ‘¨β€πŸ« : Prof. Shankar Narasimhan, Prof. Ragunathan Rengasamy πŸ”— https://nptel.ac.in/courses/106106179 #Data_Science #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
13 906
Data Science Components
Data Science Components