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Data Science & Machine Learning

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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

Red: Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT ExpertIndia3 825Educación2 015...

📈 Análisis del canal de Telegram Data Science & Machine Learning

El canal Data Science & Machine Learning (@datasciencefun) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 77 661 suscriptores, ocupando la posición 2 015 en la categoría Educación y el puesto 3 825 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 77 661 suscriptores.

Según los últimos datos del 12 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -123, y en las últimas 24 horas de -21, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.52%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.01% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 1 954 visualizaciones. En el primer día suele acumular 781 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 3.
Intereses temáticos: El contenido se centra en temas clave como learning, accuracy, distribution, panda, dataset.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 13 noviembre, 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 Educación.

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77 661

Suscriptores

-2124 horas

-767 días

-12330 días

1 954

Visitas de la publicación

~ 78124 horas

~ 1 03648 horas

2.52%

Tasa de compromiso

~ 2

Mensajes por día

Ads index

Archivo de publicaciones

77 661

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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Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals PDF

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🚀Join our first free lessons and explore the fields of tech! You will find the answers to all your questions at our webinars. Open the link https://crst.co/imKOy, make your choice and apply now while there are still seats available. See you there! ▶️ May 26 - Manual QA Course. Free first lesson! ▶️ May 26 - Best Tech Remote Careers 2022: Systems Engineer ▶️ June 2 - Systems Engineer. Free first lesson! Special offer for all participants! ️✅ Apply by the link https://crst.co/mwOgo

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Python for Data Science: The Ultimate Step-by-Step Guide to Learn Python In 7 Days & NLP, Data Science from with Python PDF

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A LITTLE GUIDE TO HANDLING MISSING DATA Having any Feature missing more than 5-10% of its values? you should consider it to be missing data or feature with high absence rate👀 How can you handle these missing values, ensuring you dont loose important part of your data🤷‍♀️ Not a problem😌. Here are important facts you must know😉 ✍️Instances with missing values for all features should be eliminated ✍️Features with high absence rate should either be eliminated or filled with values ✍️Missing values can be replaced using Mean Imputation or Regression Imputation ✍️ Be careful with mean imputation for it may introduce bias as it evens out all instances ✍️Regression Imputation might overfit your model ✍️Mean and Regression Imputation can't be applied to Text features with missing values ✍️Text Features with missing values can be eliminated if not needed in data ✍️Important Text Features with Missing values can be replaced with a new class or category labelled as uncategorized

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Machine_Learning_andrewng.pdf4.01 MB

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To become a Machine Learning Engineer: • Python • numpy, pandas, matplotlib, Scikit-Learn • TensorFlow or PyTorch • Jupyter, Colab • Analysis > Code • 99%: Foundational algorithms • 1%: Other algorithms • Solve problems ← This is key • Teaching = 2 × Learning • Have fun!

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GIT Cheatsheet.pdf0.70 KB

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Data Engineering with AWS PDF

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Big data notes.pdf2.89 MB

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#numpy NumPy Smart use of ‘:’ to extract the right shape Sometimes you encounter a 3-dim array that is of shape (N, T, D), while your function requires a shape of (N, D). At a time like this, reshape() will do more harm than good, so you are left with one simple solution: Example:

for t in xrange(T):
  x[:, t, :] = # ...

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📕 Introduction to Machine Learning by Alex Smola and S.V.N. Vishwanathan University Press, Cambridge

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thebook_ Introduction to Machine Learning.pdf10.31 MB

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Expert_Python_Programming_Master_Python_by_learning_the_best_coding.epub4.52 MB

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Pattern Recognition and Machine Learning.pdf4.52 MB

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Pattern Recognition and Machine Learning [ Information Science and Statistics ] Christopher M. Bishop #python #machinelearning #statistics #information #ai #ml

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Follow the latest IT, computer science and entrepreneurship news on Hacker News Digest Telegram channel Hacker News (news.ycombinator.com) – is one of the most influential social news websites. It was here that Drew Houston first introduced Dropbox to the world. Hacker News Digest Telegram channel will send you the top 10 most popular posts from Hacker News, daily. Subscribe to stay up-to-date!

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SQL handwritten notes .pdf1.37 MB

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SQL Tips and Tricks for Data Science.zip147.63 MB

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Numpy_Python_Cheat_Sheet.pdf6.49 KB