Data science/ML/AI

前往频道在 Telegram

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 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

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网络:Programming, data science, ML - free courses by Big Data Specialist 印度31 551 技术与应用9 384...

📈 Telegram 频道 Data science/ML/AI 的分析概览

频道 Data science/ML/AI (@datascience_bds) 英语语言赛道中的是活跃参与者。目前社区聚集了 13 690 名订阅者，在 技术与应用 类别中位列第 9 384，并在印度地区排名第 31 551 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 13 690 名订阅者。

根据 11 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 150，过去 24 小时变化为 11，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 8.13%。内容发布后 24 小时内通常能获得 2.20% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 1 112 次浏览，首日通常累积 301 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 5。
主题关注点： 内容集中在 panda, learning, row, api, ethic 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“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 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

凭借高频更新（最新数据采集于 12 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

13 690

订阅者

+1124 小时

+227 天

+15030 天

1 112

帖子浏览量

~ 30124 小时

~ 43548 小时

8.13%

参与率

~ 1

每日帖子数

Ads index

beta

帖子存档

13 690

Amazing Hackthon Solved Data Science/ML Project Collection ⭐️ 167 https://github.com/analyticsindiamagazine/MachineHack/tree/master/Hackathon_Solutions

13 690

Photoshop detector AI called FALDetector aims to detect facial edits that warps the faces to make chin or jaw looks thinner, or the forehead smaller. However, it is not really accurate and consistent as it look at the individual pixels too much, as different resolution of the same person can result in different predictions with this AI model. FALDetector: Github: https://github.com/peterwang512/FALdetector Project page: https://peterwang512.github.io/FALdetector/ Installation tutorial: https://www.youtube.com/watch?v=fZSWAsjwQpE Paper: https://arxiv.org/pdf/1906.05856.pdf

13 690

Gently down the stream A gentle introduction to Apache Kafka Written and illustrated by Mitch Seymor Learn about Kafka in a way i am sure you haven't seen before 😊 https://www.gentlydownthe.stream/

13 690

super-cheatsheet-machine-learning-2.pdf1.26 MB

13 690

Data Preparation in SQL, with Cheat Sheet!

13 690

Deep learning with Python: ⭐️ 12.9k https://github.com/fchollet/deep-learning-with-python-notebooks Join @github_repositories_bds for more cool repositories. *This channel belongs to @bigdataspecialist group

13 690

How to choose a database-type and technology for your project:

13 690

Machine Learning University: Accelerated Natural Language Processing Class 1.6k stars 368 forks https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp Join @github_repositories_bds for more cool repositories. *This channel belongs to @bigdataspecialist group

13 690

Fully Connected Neural Networks with Keras n this course, we'll build three different neural networks with Keras, using Tensorflow for the backend. Keras is a high level API for building neural networks, and makes it very easy to get started with only a few lines of code. 🔗 Neural Networks with Keras free course link

13 690

Dannjs - Easy Deep Neural Networks for the Web 🔗 https://dannjs.org

13 690

Free Tableau ebook for data visualization

13 690

👩‍🎓Online lectures on Special Topics in AI: Deep Learning Fresh free and open playlist on special topics in #DL from University of Wisconsin-Madison. Topics covering reliable deep learning, generalization, learning with less supervision, lifelong learning, deep generative models and more. Overview Lecture: https://www.youtube.com/watch?v=6LSErxKe634&list=PLKvO2FVLnI9SYLe1umkXsOfIWmEez04Ii YouTube Playlist: https://www.youtube.com/playlist?list=PLKvO2FVLnI9SYLe1umkXsOfIWmEez04Ii Syllabus: http://pages.cs.wisc.edu/~sharonli/courses/cs839_fall2020/schedule.html #wheretostart #lectures #YouTube

13 690

One of the most comprehensive cheatsheets on Machine Learning and Data Science. It covers all the essential topics.

13 690

41 Essential Machine Learning Interview QnAs-1.pdf8.07 KB

13 690

Great GitHub repository containing many Google colabs with latest's Deep Learning Models *Text-to-speach *Speech recognition *Object detection *Pose detection *Segmentation *GANs https://github.com/tugstugi/dl-colab-notebooks

13 690

Free ML crash course by Google https://developers.google.com/machine-learning/crash-course/

13 690

PDF from previous repository.

13 690

GitHub repo containing machine learning cheatsheet with code: https://github.com/soulmachine/machine-learning-cheat-sheet 👉 @bigdataspecialist

13 690

Machine learning.pdf5.31 MB

13 690

Core machine learning concepts explained through memes and simple charts. This 120-pages pdf document is created by Mihail Eric.