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 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist
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Red:📈 Análisis del canal de Telegram Data science/ML/AI
El canal Data science/ML/AI (@datascience_bds) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 905 suscriptores, ocupando la posición 8 911 en la categoría Tecnologías y Aplicaciones y el puesto 28 819 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 905 suscriptores.
Según los últimos datos del 30 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 90, y en las últimas 24 horas de 7, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 7.35%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 2.05% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 022 visualizaciones. En el primer día suele acumular 285 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 5.
- Intereses temáticos: El contenido se centra en temas clave como panda, learning, row, api, ethic.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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...”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 31 agosto, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
13 905
Suscriptores
+724 horas
+17 días
+9030 días
Archivo de publicaciones
13 906
20 AWESOME SOURCES OF FREE DATA SETS
If you are after solid data to do your projects with ease and lessen the stress of doing the data collection yourself, here's a good resource containing amazing sites where you can get your data sets for free😁
https://www.searchenginejournal.com/free-data-sources/302601/#close
13 906
The Machine Learning Crash Course With TensorFlow APIs
Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.
Link: **https://developers.google.com/machine-learning/crash-course
**Contents:
🔘 30+ Exercises
🔘 25 Lessons
🔘 15 hours course duration
🔘 Lectures from Google Researchers
🔘 Real World Case Studies
🔘 Interactive Visualisation of Algorithms in action
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*This channel belongs to @bigdataspecialist group
13 906
2022 Python and Machine Learning in Financial Analysis
Looking to improve your machine learning skills for financial analysis? Here's a free resource for you😉
Rating⭐️: 4.3 out 5
Students 👨🎓 : 33,014
Duration ⏰ : 20 hours on-demand video
Teacher 👨🏫: S.Emadedin Hashemi
Course Link
This course coupon expires until 3rd of May. Let's jump on this while we still can😁
#machinelearning #pythoncourses #python
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13 906
Best of Machine Learning with Python
Here's a ranked list of 920 awesome machine learning projects with a total of 3,4 Million stars grouped into 34 categories.
Stars⭐️: 6.9K
Fork: 962
Repo: https://github.com/ml-tooling/best-of-ml-python#image-data
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13 906
Difference between AI, ML and DL
Contains a simplified guide to understanding the terms AI, ML and DL
13 906
+2Matplotlib Cheat Sheet
Contains essential MatPlotLib guide from beginners to pro
13 906
The Best Data Science Approaches In The Data Mining World
One of the best approaches in the data mining world is called the CRISP-DM. This means Cross Industry Standard Process for Data Mining. It describes the data project as having six phases.
1) Business Understanding
a) What is the business objectives and situation assessment
b) Determine the data mining goal and create a project plan
2) Data Understanding
a) Collect Initial data and describe data
b) Explore data and verify data quality
3) Data Preparation
a) Get,Select and Clean the data set
b) Construct and Integrate data
4) Modeling
a) Select model technique and generate test design
b) Build and access model
5) Evaluation
a) Evaluate and review process
b) Determine the next steps
6) Deployment
a) Plan deployment
b) Plan monitoring and maintenance
c) Produce final report and review project
13 906
Machine Learning with Python : COMPLETE COURSE FOR BEGINNERS
Complete Machine Learning Course with Python for beginners
Rating⭐️: 4.6 out 5
Students 👨🎓 : 18533
Duration ⏰ : 13 hours on-demand video
Teacher 👨🏫: Prashant Mishra
🔗 Course link
I have noticed this one is currently free (but only for first 1000 enrols !!!) so I thought some of you might be interested 😊
#machinelearning #pythoncourses #python
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13 906
The Data Science Interview Study Guide
Preparing for a job interview can be a full-time job, and Data Science interviews are no different. Here are 121 resources that can help you study and quiz your way to landing your dream data science job.
https://www.kdnuggets.com/2020/01/data-science-interview-study-guide.html
13 906
Top 8 Github Repos to Learn Data Science and Python
1. All algorithms implemented in Python
By: The Algorithms
Stars ⭐️: 135K
Fork: 35.3K
Repo: https://github.com/TheAlgorithms/Python
2. DataScienceResources
By: jJonathan Bower
Stars ⭐️: 3K
Fork: 1.3K
Repo: https://github.com/jonathan-bower/DataScienceResources
3. Playground and Cheatsheet for Learning Python
By: Oleksii Trekhleb ( Also the Image)
Stars ⭐️: 12.5K
Fork: 2K
Repo: https://github.com/trekhleb/learn-python
4. Learn Python 3
By: Jerry Pussinen
Stars ⭐️: 4,8K
Fork: 1,4K
Repo: https://github.com/jerry-git/learn-python3
5. Awesome Data Science
By: Fatih Aktürk, Hüseyin Mert & Osman Ungur, Recep Erol.
Stars ⭐️: 18.4K
Fork: 5K
Repo: https://github.com/academic/awesome-datascience
6. data-scientist-roadmap
By: MrMimic
Stars ⭐️: 5K
Fork: 1.5K
Repo: https://github.com/MrMimic/data-scientist-roadmap
7. Data Science Best Resources
By: Tirthajyoti Sarkar
Stars ⭐️: 1.8K
Fork: 717
Repo: https://github.com/tirthajyoti/Data-science-best-resources/blob/master/README.md
8. Ds-cheatsheets
By: Favio André Vázquez
Stars ⭐️: 10.4K
Fork: 3.1K
Repo: https://github.com/FavioVazquez/ds-cheatsheets
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13 906
Few Numpy Tutorials
Python NumPy Tutorial – Learn NumPy Arrays With Examples
https://www.edureka.co/blog/python-numpy-tutorial/
Python Numpy Tutorial (with Jupyter and Colab)
https://cs231n.github.io/python-numpy-tutorial/
NumPy fundamentals (official docs)
https://numpy.org/doc/stable/user/basics.html
#numpy
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