Algorithms for Massive Data
PDF: https://arxiv.org/pdf/2301.00754
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PDF: https://arxiv.org/pdf/2301.00754
https://www.tgoop.com/DataScienceM
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Forwarded from Python | Machine Learning | Coding | R
This channels is for Programmers, Coders, Software Engineers.
0οΈβ£ Python
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100 Important Data Science Interview Questions.pdf
11.7 MB
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Foundations of Large Language Models
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Download it: https://readwise-assets.s3.amazonaws.com/media/wisereads/articles/foundations-of-large-language-/2501.09223v1.pdf
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Master PyTorch Faster with These Free Resources!
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2. Learn PyTorch Deep Learning with Hands-On Code
A beginner-friendly PDF with practical examples to help you build and train deep learning models using PyTorch from scratch.
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Download:
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2. Learn PyTorch Deep Learning with Hands-On Code
A beginner-friendly PDF with practical examples to help you build and train deep learning models using PyTorch from scratch.
Download:
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Datasets Guide π
A practical and beginner-friendly guide that walks you through everything you need to know about datasets in machine learning and deep learning. This guide explains how to load, preprocess, and use datasets effectively for training models. It's an essential resource for anyone working with LLMs or custom training workflows, especially with tools like Unsloth.
Importance:
Understanding how to properly handle datasets is a critical step in building accurate and efficient AI models. This guide simplifies the process, helping you avoid common pitfalls and optimize your data pipeline for better performance.
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A practical and beginner-friendly guide that walks you through everything you need to know about datasets in machine learning and deep learning. This guide explains how to load, preprocess, and use datasets effectively for training models. It's an essential resource for anyone working with LLMs or custom training workflows, especially with tools like Unsloth.
Importance:
Understanding how to properly handle datasets is a critical step in building accurate and efficient AI models. This guide simplifies the process, helping you avoid common pitfalls and optimize your data pipeline for better performance.
Link: https://docs.unsloth.ai/basics/datasets-guide
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Open Guide to Data Structures and Algorithms
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Read it here:
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A must-read for anyone starting their journey in computer science and programming. This open-access book offers a clear, beginner-friendly introduction to the core concepts of data structures and algorithms, with simple explanations and practical examples. Whether you're a student or a self-learner, this guide is a solid foundation to build your DSA knowledge. Highly recommended for those who want to learn efficiently and effectively.
Read it here:
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Access whitepapers, podcasts, code labs, & recorded livestreams. Additionally, there is a bonus assignment for you!
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Kaggle
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A Complete Course to Learn Robotics and Perception
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson
github.com/gtbook/robotics
roboticsbook.org/intro.html
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github.com/gtbook/robotics
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Explore the comprehensive world of Reinforcement Learning (RL) with this authoritative textbook by Dimitri P. Bertsekas. This book offers an in-depth overview of RL methodologies, focusing on optimal and suboptimal control, as well as discrete optimization. It's an essential resource for students, researchers, and professionals in the field.
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ML Tools GRadio.pdf
203.3 KB
Gradio: The easiest way to demo your models.
- Core Idea: Quickly turn #ML models into interactive web apps.
- No frontend skills needed. It's all #Python.
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β»οΈ Repost if you found this useful
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- Core Idea: Quickly turn #ML models into interactive web apps.
- No frontend skills needed. It's all #Python.
- Works with any Python code, including custom functions.
- Share via temporary links or deploy on #HuggingFace Spaces.
- Get user feedback to improve your models.
If you're looking to create interactive demos for your ML project, check out #Gradio!
β»οΈ Repost if you found this useful
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