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

10 Jan, 16:01


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Repositorio data science

13 Dec, 04:31


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Repositorio data science

26 Nov, 12:34


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Repositorio data science

26 Nov, 11:47


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Repositorio data science

20 Nov, 22:36


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Repositorio data science

19 Nov, 19:49


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Repositorio data science

12 Nov, 05:21


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Repositorio data science

12 Nov, 02:25


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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.
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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.
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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.

Repositorio data science

06 Nov, 05:34


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Repositorio data science

06 Nov, 02:19


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Python For Data Science A-Z: EDA With Real Exercises

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Repositorio data science

04 Nov, 13:22


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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


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Repositorio data science

20 Oct, 22:25


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Repositorio data science

20 Oct, 21:14


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Repositorio data science

19 Oct, 05:41


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Repositorio data science

02 Oct, 01:56


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Repositorio data science

24 Sep, 16:48


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Repositorio data science

16 Sep, 14:09


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Repositorio data science

15 Sep, 02:57


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Repositorio data science

13 Sep, 01:44


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Repositorio data science

13 Sep, 01:08


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Repositorio data science

11 Sep, 22:47


🐶
Hey chicos, les pedimos disculpas porque en el día de ayer se rompió nuestro server 😵 de @freecoupons_reposcience. Después de chequear algunos ajustes de configuración, nos complace anunciar que ya vuelve a estar activo.💯
Gracias por su paciencia

Repositorio data science

10 Sep, 09:51


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Repositorio data science

03 Sep, 04:00


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Repositorio data science

01 Sep, 11:45


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Repositorio data science

28 Aug, 09:47


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