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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

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📈 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 77 677 suscriptores, ocupando la posición 2 014 en la categoría Educación y el puesto 3 822 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 77 677 suscriptores.

Según los últimos datos del 11 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -97, y en las últimas 24 horas de -12, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.59%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.99% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 2 009 visualizaciones. En el primer día suele acumular 767 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 12 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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77 677

Suscriptores

-1224 horas

-647 días

-9730 días

2 009

Visitas de la publicación

~ 76724 horas

~ 1 03648 horas

2.59%

Tasa de compromiso

~ 1

Mensajes por día

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Archivo de publicaciones

77 661

Artificial Intelligence for Games.pdf17.63 MB

77 661

Mastering Machine Learning for Penetration Testing.epub8.95 MB

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Data Analysis Interterview Questions and Answers 👇👇 1.How to create filters in Power BI? Filters are an integral part of Power BI reports. They are used to slice and dice the data as per the dimensions we want. Filters are created in a couple of ways. Using Slicers: A slicer is a visual under Visualization Pane. This can be added to the design view to filter our reports. When a slicer is added to the design view, it requires a field to be added to it. For example- Slicer can be added for Country fields. Then the data can be filtered based on countries. Using Filter Pane: The Power BI team has added a filter pane to the reports, which is a single space where we can add different fields as filters. And these fields can be added depending on whether you want to filter only one visual(Visual level filter), or all the visuals in the report page(Page level filters), or applicable to all the pages of the report(report level filters) 2.How to sort data in Power BI? Sorting is available in multiple formats. In the data view, a common sorting option of alphabetical order is there. Apart from that, we have the option of Sort by column, where one can sort a column based on another column. The sorting option is available in visuals as well. Sort by ascending and descending option by the fields and measure present in the visual is also available. 3.How to convert pdf to excel? Open the PDF document you want to convert in XLSX format in Acrobat DC. Go to the right pane and click on the “Export PDF” option. Choose spreadsheet as the Export format. Select “Microsoft Excel Workbook.” Now click “Export.” Download the converted file or share it. 4. How to enable macros in excel? Click the file tab and then click “Options.” A dialog box will appear. In the “Excel Options” dialog box, click on the “Trust Center” and then “Trust Center Settings.” Go to the “Macro Settings” and select “enable all macros.” Click OK to apply the macro settings. ————————————————————- ENJOY LEARNING 👍👍

77 661

Machine Learning Fundamentals: A Concise Introduction PDF

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Which of the following tool can be used for data visualization?

Anonymous voting

77 661

Python for data science 2022.pdf2.42 MB

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Artificial Intelligence in Games PDF

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Python For Data Science 2022 PDF

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Fundamentals_of_Deep_Learning,_2nd_Edition_Fourth_Early_Release.pdf10.94 MB

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Deep Learning Masterpiece .pdf14.46 MB

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Distributed Machine Learning with Python PDF

77 661

Introduction to R Programming👉

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New Data Scientists - When you learn, it's easy to get distracted by Machine Learning & Deep Learning terms like "XGBoost", "Neural Networks", "RNN", "LSTM" or Advanced Technologies like "Spark", "Julia", "Scala", "Go", etc. Don't get bogged down trying to learn every new term & technology you come across. Instead, focus on foundations. - data wrangling - visualizing - exploring - modeling - understanding the results. The best tools are often basic, Build yourself up. You'll advance much faster. Keep learning!

77 661

The Machine Learning Solutions Architect Handbook PDF

77 661

Data Engineering with Google Cloud Platform PDF

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Machine Learning Mastery with Python: Understand Your Data, Create Accurate Models and Work Projects End-to-end PDF

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Numpy Handbook.pdf3.75 KB

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Probability Cheat Sheet 👇👇 Cheat Sheet

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💥Deep Learning with Pytorch by Prof.Yann LeCun (CNN Founder) This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. GitHub Link: https://atcold.github.io/pytorch-Deep-Learning/ YouTube Playlist: https://www.youtube.com/playlist?list=PLLHTzKZzVU9eaEyErdV26ikyolxOsz6mq