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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 821Educación2 017...

📈 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 77 621 suscriptores, ocupando la posición 2 017 en la categoría Educación y el puesto 3 821 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 77 621 suscriptores.

Según los últimos datos del 13 noviembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -142, y en las últimas 24 horas de -20, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 2.37%. 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 1 843 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 14 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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77 621

Suscriptores

-2024 horas

-957 días

-14230 días

1 843

Visitas de la publicación

~ 78124 horas

~ 1 05048 horas

2.37%

Tasa de compromiso

~ 2

Mensajes por día

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Archivo de publicaciones

77 621

Artificial Neural Networks with Java

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LinkedIn - Python for Data Science Essential Training Part 2.zip390.08 MB

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🌐 Join the researchers and programmers channel (Courses, Books, Papere and Codes). t.me/DataScience_Books

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Advanced ML with Python

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Introduction to Data Science - A Python Approach to Concepts, Techniques and Applications - Laura Igual, Santi Segui (Springer, 2017)

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What is unsupervised learning? Unsupervised learning aims to detect patterns in the data where no labels are given.

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Tableau_Cheatsheet.pdf1.65 KB

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git-cheat-sheet-education.pdf0.98 KB

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What are precision, recall, and F1-score? Precision and recall are classification evaluation metrics: P = TP / (TP + FP) and R = TP / (TP + FN). Where TP is true positives, FP is false positives and FN is false negatives In both cases the score of 1 is the best: we get no false positives or false negatives and only true positives. F1 is a combination of both precision and recall in one score (harmonic mean): F1 = 2 * PR / (P + R). Max F score is 1 and min is 0, with 1 being the best.

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How NASA Auto Colourise Images with Deep Learning? Free Live Sessions on Aug 19th,20th @7.00pm IST Register here : https://bit.ly/2SLpFlw

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Machine Learning God by Stefan Stavrev (version 2.0).pdf1.57 MB

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Some useful Machine Learning projects for practice https://elitedatascience.com/machine-learning-projects-for-beginners https://hackernoon.com/top-5-machine-learning-projects-for-beginners-47b184e7837f https://www.springboard.com/blog/machine-learning-projects https://www.ubuntupit.com/top-20-best-machine-learning-projects-for-beginner-to-professional

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Learn how Amazon Optimise Delivery Routes using Genetic Algorithm 👇👇 https://bit.ly/3izxvZJ Free Live Session with Certificate

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Some interview questions related to Data science 1- what is difference between structured data and unstructured data. 2- what is multicollinearity.and how to remove them 3- which algorithms you use to find the most correlated features in the datasets. 4- define entropy 5- what is the workflow of principal component analysis 6- what are the applications of principal component analysis not with respect to dimensionality reduction 7- what is the Convolutional neural network. Explain me its working

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🤓 Technical Python concepts tested in the data science job interviews are: - Data types. - Built-in data structures. - User-defined data structures. - Built-in functions. - Loops and conditionals. - External libraries (Pandas). Source Article: https://www.kdnuggets.com/2021/07/top-python-data-science-interview-questions.html

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What are the benefits of a single decision tree compared to more complex models? easy to implement fast training fast inference good explainability

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What are the decision trees? This is a type of supervised learning algorithm that is mostly used for classification problems. Surprisingly, it works for both categorical and continuous dependent variables. In this algorithm, we split the population into two or more homogeneous sets. This is done based on most significant attributes/ independent variables to make as distinct groups as possible. A decision tree is a flowchart-like tree structure, where each internal node (non-leaf node) denotes a test on an attribute, each branch represents an outcome of the test, and each leaf node (or terminal node) holds a value for the target variable. Various techniques : like Gini, Information Gain, Chi-square, entropy.

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What is feature selection? Why do we need it? Feature Selection is a method used to select the relevant features for the model to train on. We need feature selection to remove the irrelevant features which leads the model to under-perform.

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The session is going to go LIVE in 5 mins So join in now ! Link - https://youtu.be/a8lGmSLcfWU

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Do you want to Learn how to build a winning resume ? Learn the basics from an expert in our mentor conference 2021 Resume session today! Link to Join - https://youtu.be/a8lGmSLcfWU If you are interested in getting a certificate and resources then kindly register at www.foreignadmits.com/mentorconference2021 Note - Certificates will only be given to registered LIVE attendees See you at the mentor conference Join our community to get updates about other sessions - https://t.me/foreignadmits_community