#PyTorch tutorial
84 related articles
Tutorials·3 min
PyTorch Beginner Tutorial: A Complete Guide to Tensor Operations and Neural Network Construction
A detailed PyTorch beginner guide covering tensor operations, dynamic computational graphs, GPU acceleration, and building your first neural network with nn.Module, with learning path recommendations and code examples.
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·4 min
SELENE Open-Source Project: An Interactive Notebook Library for Systematically Learning AI and Machine Learning from Scratch
SELENE is an open-source AI learning resource built on Jupyter Notebooks, systematically covering ML, deep learning, Transformers, and LLMs with interactive code and math derivations for beginners.
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·4 min
How Much Math Do You Need for Machine Learning? Finding the Balance Between Preparation and Practice
How much math do you really need before starting ML projects? This article analyzes the 'bottomless pit' trap, proposes a minimum viable math framework, and offers project-driven learning strategies.
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·2 min
awesome-systematic-trading: A Complete Guide to the 9,000-Star Quantitative Trading Open Source Resource List
Deep dive into the 9,100-star awesome-systematic-trading GitHub project covering backtesting frameworks, strategy implementations, data tools, and classic books for quantitative traders.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·3 min
DeepSeek-OCR Deployment & Fine-Tuning in Practice: From vLLM Inference to Unsloth Fine-Tuning
Complete guide to DeepSeek-OCR from vLLM inference deployment and Unsloth model loading to fine-tuning, covering cloud server setup, GPU selection, and code examples — all on a single 4090 GPU.
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·2 min
RX 9060 XT vs RTX 5060 Ti: How to Choose a GPU for Local AI
RX 9060 XT vs RTX 5060 Ti both offer 16GB VRAM — which is better for local AI inference? A full comparison of CUDA ecosystem, ROCm compatibility, LLM performance, and real-world usability.
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·2 min
RX 9060 XT vs RTX 5060 Ti: Which GPU to Pick for Local AI?
RX 9060 XT vs RTX 5060 Ti — both 16GB VRAM, but which is better for local AI? We compare CUDA ecosystem, ROCm compatibility, LLM inference, and real-world usability.
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·2 min
From Zero to AI Career: A Complete Breakdown of a 3-Month Self-Study Roadmap
Want to break into AI from scratch? This article breaks down an efficient self-study roadmap: from Python, math, and machine learning basics to PyTorch, then to CV, NLP, and data mining—reaching entry-level career-switching intensity in 3 months.
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CS Self-Study Guide: The 74K-Star Comp…
·2 min
CS Self-Study Guide: The 74K-Star Computer Science Learning Roadmap
A 74K-star GitHub project by Peking University students curates MIT, Stanford, and CMU open courses into a complete CS self-study roadmap covering algorithms, OS, databases, and more.
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·3 min
Don't Start AI Learning with Machine Learning: A Beginner's Guide to the Onion Model
Gaurav Sen reveals the fatal trap in AI learning: starting from ML fundamentals often leads to burnout. Learn the Onion Model approach—RAG, Agents first, Transformers next, math last.
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·3 min
How to Choose AI Learning Books: A 5-Dimension Rational Evaluation Framework
How to evaluate AI/ML books rationally? Use these 5 dimensions—content depth, code quality, currency, community reputation, and companion resources—to choose wisely.
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·3 min
Building a Transformer from Scratch: A PyTorch Hands-On Guide for Self-Taught Developers
A self-taught developer with 2 years of Python experience implements Transformer from scratch using plain PyTorch, following the original 'Attention Is All You Need' paper with a two-phase approach: inference first, then full training.
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·3 min
Math Learning Path for Machine Learning: From Resource Overload to Systematic Mastery
Overwhelmed by ML math courses? This guide maps out linear algebra, calculus, and probability into a practical learning path — from core courses to reference books.
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Building AI Engineering Skills from Sc…
·2 min
Building AI Engineering Skills from Scratch: A Deep Dive into the Viral GitHub Learning Path
A deep dive into 'ai-engineering-from-scratch,' the GitHub project with 38K+ stars that helps developers build real AI engineering skills through a Learn-Build-Ship methodology.
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·3 min
Java Developers Transitioning to AI: A Practical Guide to Building RAG Knowledge Bases
How can Java developers break into AI? This guide covers the AI application engineer career path, RAG knowledge base fundamentals, vector database retrieval, and enterprise-grade RAG challenges.
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GitHub Daily · July 18: 3D Reconstruct…
·3 min
GitHub Daily · July 18: 3D Reconstruction Foundation Model Tops the Charts, AI Engineering and CLI Agents Explode Collectively
July 18 GitHub Daily: 3D reconstruction foundation model lingbot-map tops the charts, with AI engineering tooling, CLI Agents, and the MCP ecosystem exploding across the board.
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·2 min
Transitioning to AI/ML: Why Finding a Study Buddy Matters More Than Picking the Right Course
Transitioning from software dev to AI/ML is hard to do alone. Discover why finding a study buddy beats picking the perfect course — and how peer accountability solves the consistency, judgment-free questioning, and foundation-building challenges.
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·2 min
AI Large Model Learning Roadmap: A Complete Five-Stage Guide from Zero to Independent Deployment
A complete 5-stage AI large model learning roadmap — from Python basics and prompt engineering to RAG pipelines, Agent development, and private model deployment.
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·2 min
A Beginner's Guide to Grokking Machine Learning: Self-Study Paths and Resource Recommendations
Why Grokking Machine Learning is a top pick for ML beginners — covering the author, content, legal access options, and an effective self-study roadmap.
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