#MATLAB AI programming
11 related articles
·3 min
DeepSeek + MATLAB: Zero-Barrier AI Auto-Programming and Debugging
Learn how to call the DeepSeek API in MATLAB for AI auto-programming and debugging. From API key setup to building an auto-debug inner loop, a complete guide with a linear fitting demo.
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The Complete AI Researcher Learning Ro…
·3 min
The Complete AI Researcher Learning Roadmap: A Beginner's Guide to Deep Learning
A structured AI/ML learning roadmap covering Python, math, machine learning, deep learning, and MLOps — with timelines, milestones, and free resource recommendations.
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·5 min
Complete Guide to the National Mathematical Modeling Contest: Modeling, Topic Selection, and Award-Winning Strategies in the AI Era
A comprehensive guide to preparing for the National Mathematical Modeling Contest: covering the essence of modeling, judging rules, topic selection, AI usage guidelines, and a four-day schedule to boost your chances of winning.
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·4 min
How to Choose a Machine Learning Course for Beginners: A Complete Roadmap
Not sure where to start with machine learning? This guide covers the community-approved ML roadmap: from math and Python basics to Andrew Ng, fast.ai, Kaggle, and CS229.
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·3 min
DeepSeek + Claude Code: A Deep Dive into How AI Automatically Builds Simulink Models
A deep dive into how DeepSeek and Claude Code automatically build Simulink models, explaining the roles of five core tools and their collaboration logic.
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·3 min
PyTorch Beginner's Guide: A Complete Analysis of Deep Learning Framework Selection and Evolution
A comprehensive analysis of why PyTorch became the most mainstream deep learning framework. Covers framework history, comparisons with TensorFlow and Keras, dynamic graphs, Tensors, installation guide, and cloud trends.
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Tutorials·4 min
Machine Learning for Absolute Beginners: A Complete Learning Path from Overview to Practice
A beginner-friendly machine learning tutorial covering AI overview, NumPy, Pandas, Matplotlib, and hands-on cases. Master ML fundamentals in three days through five systematic modules.
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Tutorials·3 min
Universal AI Prompts for Mathematical Modeling: A Zero-to-Hero Four-Stage Practical Guide
A detailed guide to the four-stage universal AI prompt system for mathematical modeling, covering problem analysis, innovative model construction, data processing, and model solving for competitions.
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Tutorials·3 min
Python Learning Path: A Three-Stage Systematic Approach from Zero to Practical Projects
A detailed guide to Python's three learning stages: syntax fundamentals, advanced concepts, and practical applications. Covers OOP, web scraping, data analysis, and automation with timeline planning.
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Product Reviews·4 min
Kimi K2 Thinking Hands-On Review: Can It Replace Sonnet 4.5 in Claude Code?
Hands-on testing Kimi K2 Thinking in Claude Code across text creation, programming, agent building, and full-stack apps. Comparing it to Claude Sonnet 4.5 and DeepSeek as a cost-effective AI coding alternative.
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Tutorials·4 min
STM32 Smart Car Development: Where Does AI-Assisted Programming Hit Its Limits?
A deep dive into an STM32F103C8T6 HAL library AI smart car course, exploring AI's real capabilities and three key limitations in embedded development, and the best practices for human-AI collaboration.
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