#backpropagation
199 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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Deep Dives·1 min
Neural Networks for Beginners: From Fundamentals to Handwritten Digit Recognition
Understand neural networks from scratch. Learn input layers, hidden layers, forward propagation, backpropagation, gradient descent, with a handwritten digit recognition example.
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Expert Opinions·1 min
Karpathy on Vibe Coding and Agentic Engineering: A Paradigm Shift for Programmers
Karpathy explains the paradigm shift from vibe coding to agentic engineering, how LLMs reshape programming in the Software 3.0 era, and why verifiability matters.
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Industry Insights·1 min
Karpathy Joins Anthropic: An Industry Shift from Vibe Coding to Agentic Engineering
AI leader Andrej Karpathy officially joins Anthropic's pretraining team, marking his evolution from Vibe Coding to Agentic Engineering and a return to frontier AI research.
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Tutorials·2 min
Deep Learning Beginner Tutorial: From Neural Network Fundamentals to Image Recognition in Three Days
A systematic review of a three-day deep learning crash course covering neural network math, gradient descent, backpropagation, TensorFlow, CNNs, and transfer learning with practical tips.
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Product Reviews·2 min
DeepSeek V4 Coding Test: Top-Ranked Kimi Fails, Claude Remains the Strongest
Real coding test of DeepSeek V4, Claude Opus, GPT, and Kimi K2.6 on the same full-stack game task. Top-ranked Kimi K2.6 fails completely while Claude succeeds first try.
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Expert Opinions·2 min
AI Godfather Hinton's Latest Warning: AI Has Learned to Deceive, Programmers Will Be Replaced
Nobel laureate Hinton warns in CNN interview that AI has learned deception and self-preservation, predicts programmers will be replaced at scale, and criticizes OpenAI and Meta for neglecting safety.
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Tutorials·2 min
Python Machine Learning in Practice: A Complete Guide from Algorithm Derivation to Code Implementation
A systematic Python ML course using a 3-stage framework: algorithm derivation, code implementation, and experimental analysis. Covers logistic regression, decision trees, and ensemble learning.
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Product Reviews·4 min
Hugging Face Transformers: Deep Dive into the 160K-Star Open Source AI Model Framework
Deep dive into Hugging Face Transformers: architecture, multimodal support, ecosystem, and trends. Learn how this 160K-Star project became essential for AI developers.
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Deep Dives·3 min
Google TPU v8t and v8i Deep Dive: The New Era of Separated Training and Inference AI Chips
Google Cloud Next unveils TPU v8t (training) and TPU v8i (inference) chips. Deep analysis of their architecture, strategic significance, and impact on AI chip competition.
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Tutorials·4 min
2025 LLM Career Transition Roadmap: A Three-Phase Plan from Foundations → Frameworks → Real-World Projects
A systematic 2025 LLM career transition roadmap covering Python, Transformers, LangChain, LlamaIndex, RAG, Agent development, and fine-tuning across three phases achievable in 2-3 months.
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Expert Opinions·3 min
Sequoia Capital's Conversation with AI Expert: How the Von Neumann Architecture Shapes the Future of AI
Sequoia Capital's deep conversation with AI expert Konstantine explores how von Neumann's architecture and ideas profoundly shape modern AI development, from computing paradigms to the pursuit of AGI.
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Tutorials·3 min
4-bit QLoRA Fine-tuning LLaMA 3 in Practice: A Guide to Training 8 Billion Parameter LLMs on Consumer GPUs
Learn how to fine-tune LLaMA 3 8B on consumer GPUs using QLoRA and Unsloth. Covers 4-bit quantization, LoRA adaptation, Alpaca data format, training pipeline setup, and model deployment—runs on RTX 3090.
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Expert Opinions·3 min
Reinventing the Wheel: Why Building From Scratch Is the Shortcut to the Technical Frontier
Developer Andrew Quinn compressed a 3GB SQLite database into a 7MB FST file, sharing a profound insight: reinventing four or five wheels by hand beats passive study at pushing you to the technical frontier.
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Tutorials·2 min
Unsloth Tutorial: Fine-Tune LLMs Locally with 5x Speed and Massive VRAM Savings
Learn how Unsloth uses LoRA optimization and Web UI to efficiently fine-tune Gemma 4, Qwen3, DeepSeek and more on consumer GPUs, with 2-5x speed gains and 50-70% VRAM reduction.
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Tutorials·3 min
Unsloth Tutorial: Fine-Tune LLMs Locally with Multi-fold Speed Boost and 60% VRAM Savings
Unsloth is an open-source LLM fine-tuning tool with 63K GitHub stars, supporting Gemma 4, Qwen3, and DeepSeek. It achieves multi-fold training speedup and 60% VRAM reduction through kernel optimization, enabling fine-tuning on consumer GPUs.
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Product Reviews·2 min
Unsloth: The Open-Source Tool for Fine-Tuning LLMs on a Single GPU with 70% Less VRAM
Unsloth is an open-source LLM fine-tuning tool with 63K+ GitHub stars. Fine-tune Gemma 4, Qwen 3, DeepSeek on a single RTX 3090 with 70% less VRAM, 2-5x faster training, and an intuitive Web UI.
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Product Reviews·4 min
Unsloth: The Efficient Tool for Local Open-Source LLM Training — The Secret Behind 60K+ GitHub Stars
In-depth analysis of Unsloth, a 60K+ star open-source LLM training tool supporting Gemma 4, Qwen3, DeepSeek local fine-tuning with LoRA/QLoRA to dramatically reduce VRAM requirements.
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