Algorithms for Massive Data

PDF: https://arxiv.org/pdf/2301.00754

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This channels is for Programmers, Coders, Software Engineers.

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Cheatsheet Machine Learning Algorithms

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This channels is for Programmers, Coders, Software Engineers.

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1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
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💧 18 of the best blogs to start and grow on your data science path!


👨🏻‍💻 If I were to start my data journey all over again, I would follow these 18 blogs without a break!

💬 The path to growth in data has nothing to do with your starting point, what matters is how consistently you learn.

✅ These blogs are like a mentor in your email; every week a new insight, a learning, a new idea. 👇


🥵 The Data Hustle Blog

⏪ Real experiences from the world of data in a friendly tone.

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🥵 Diving Into Data Blog

⏪ Summarizing data-heavy concepts in simple language.

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⏪ A guide to professional growth in the field of technology and data.

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🥵 To Be a Data Scientist Blog

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⏪ Continuous learning and golden tips for data scientists.

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🥵 Data Marks Blog

⏪ An excellent compilation of useful resources and tools in the world of data.

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⏪ Building a personal brand and growing in the technology space.

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⏪ System design and technical concepts for every data engineer.

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🥵 The Neural Maze Blog

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🥵 Non-Brand Data Blog

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Master PyTorch Faster with These Free Resources!
Whether you're just getting started with PyTorch or looking to refresh your deep learning skills, these two resources are all you need:

1. PyTorch Cheatsheet
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Datasets Guide 📚

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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Open Guide to Data Structures and Algorithms

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.

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📕 A Course in Reinforcement Learning by Dimitri P. Bertsekas

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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