Repositorio data science @repo_science Channel on Telegram

Repositorio data science

@repo_science

@repo_science: El canal tiene como objetivo ayudarte en el proceso de aprendizaje y educación, a través, de la busqueda exahustiva de recursos gratuitos de internet.
Que estás esperando ÚNETE a nuestra comunidad!!

Repositorio data science (Spanish)

¡Únete al canal @repo_science! Este canal tiene como objetivo ayudarte en el proceso de aprendizaje y educación en el campo de la ciencia de datos. En @repo_science, nos dedicamos a buscar exhaustivamente recursos gratuitos de internet que te permitirán ampliar tus conocimientos en este apasionante campo. Si estás interesado en aprender más sobre data science, este es el lugar perfecto para ti. No pierdas más tiempo buscando información dispersa por la web, únete a nuestra comunidad y accede a todo lo que necesitas de manera organizada y fácil de encontrar. ¿Qué estás esperando? ¡Únete a @repo_science y comienza tu viaje de aprendizaje en data science hoy mismo! 🚀

Repositorio data science

26 Nov, 12:34

#free #ProgrammingLanguages
🎟
R Programming: Aprende a programar en R desde cero

👥Students: 85307
⭐️Ratings: 4.68
⏳ 6.5 total hours
🌐 es_LA
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Repositorio data science

26 Nov, 11:47

#free #DataAnalytics
🎟
Curso Power BI: Funciones DAX + ChatGPT, mapas y gráficos

👥Students: 23886
⭐️Ratings: 4.31
⏳ 10.5 total hours
🌐 es_LA
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Repositorio data science

19 Nov, 19:49

#free #DataScience
🎟
PyTorch Ultimate 2024: From Basics to Cutting-Edge

👥Students: 19007
⭐️Ratings: 4.63
⏳ 19 total hours
🌐 en_US
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Repositorio data science

09 Nov, 12:31

Fundamental Concepts: Start with understanding the core concepts of machine learning, including supervised and unsupervised learning, model training, and evaluation metrics.
Programming Proficiency: Develop strong programming skills in Python, the most popular language for machine learning. Learn essential libraries like NumPy, Pandas, and Scikit-learn.
Data Handling and Preprocessing: Master data cleaning, handling missing values, normalization, and feature engineering to prepare data for model training.
Statistical Foundations: Gain a solid understanding of probability, statistics, and linear algebra, as these form the mathematical basis of many machine learning algorithms.
Supervised Learning Algorithms: Learn about popular algorithms like linear regression, logistic regression, decision trees, and random forests for classification and regression tasks.
Unsupervised Learning Algorithms: Explore techniques like clustering (K-means, hierarchical clustering) and dimensionality reduction (PCA) for finding patterns in unlabeled data.
Model Evaluation: Understand how to evaluate model performance using metrics like accuracy, precision, recall, F1-score, and confusion matrices.
Feature Engineering: Learn how to create new features from existing ones to improve model performance.
Hyperparameter Tuning: Explore techniques to optimize model hyperparameters for better results.
Model Deployment: Learn how to deploy models into production environments, either as standalone applications or integrated into web services.
Continuous Learning: Stay updated with the latest advancements in machine learning by following research papers, attending conferences, and participating in online communities.
Practical Experience: Gain hands-on experience by working on real-world projects and participating in Kaggle competitions.
Ethical Considerations: Understand the ethical implications of machine learning, including bias, fairness, and privacy.
Domain Knowledge: Develop expertise in a specific domain to apply machine learning effectively to real-world problems.
Collaboration and Communication: Learn to collaborate with other data scientists and communicate your findings effectively to both technical and non-technical audiences.
976
Repositorio data science

06 Nov, 05:34

#free #DataAnalytics
🎟
Microsoft Power BI: A Complete Guide

👥Students: 6215
⭐️Ratings: 4.56
⏳ 8.5 total hours
🌐 en_US
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Repositorio data science

06 Nov, 02:19

#free #DataScience
🎟
Python For Data Science A-Z: EDA With Real Exercises

👥Students: 214931
⭐️Ratings: 4.07
⏳ 16 total hours
🌐 en_US
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Repositorio data science

04 Nov, 13:22

#free #MobileApps
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Python App Development Masterclass App Development Bootcamp

👥Students: 3001
⭐️Ratings: 4.43
⏳ 6.5 total hours
🌐 en_US
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Repositorio data science

01 Nov, 00:15

🚨🚨 - Atención - 🚨🚨

Les dejamos los enlaces de invitación a los grupos asociados a nuestro canal.

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Repositorio data science

22 Oct, 02:09

#free #DataScience
🎟
Power BI Mastery: Zero to Hero Data Skills

👥Students: 20044
⭐️Ratings: 4.2
⏳ 6.5 total hours
🌐 en_US
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1,120
Repositorio data science

20 Oct, 22:25

#free #DataScience
🎟
Machine Learning & Self-Driving Cars: Bootcamp with Python

👥Students: 43834
⭐️Ratings: 4.59
⏳ 8.5 total hours
🌐 en_US
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