#ML researcher mathematics
53 related articles
·3 min
Mathematical Foundations of Machine Learning: A Complete Guide from Mitchell's Definition to the Probabilistic Perspective
A deep dive into the mathematical foundations of ML, from Tom Mitchell's classic definition (Task T, Performance P, Experience E) to Bayesian decision theory and the probabilistic perspective.
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·4 min
4-5 Month ML Job Prep Sprint: A Career Pivot Guide for Senior CS Students
How can a senior CS student pivot to ML in 4-5 months? A practical sprint guide covering learning priorities, high-quality projects, Kaggle strategy, and interview prep for fresh graduates.
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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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·3 min
How PhD Students Can Use AI for Programming Without Losing Their Coding Skills: A Layered Delegation Strategy
How can PhD students avoid coding skill atrophy when using AI programming assistants? This article proposes a layered delegation strategy with actionable advice for researchers.
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·2 min
Deep Dive into UT Austin's Online AI Master's Program: Course Intensity, Pacing, and Application Tips
Comprehensive analysis of UT Austin's online MSAI program covering course intensity, work-study balance tips, and application strategies based on real Reddit student feedback.
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·3 min
Google Launches Gemini 4 Pre-training: Its Most Ambitious AI Model Training Yet
Google DeepMind announces Gemini 4 pre-training has begun, calling it their most ambitious training yet. A deep dive into its technical direction, compute scale, multimodal breakthroughs, and competitive impact.
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·3 min
Deep Dive into the Kimi-K3 Technical Report: Architecture, Long Context, and Reasoning Capabilities
Deep analysis of Moonshot AI's Kimi-K3 technical report covering long context processing, MoE architecture, reasoning capabilities, and China's position in the global AI competition.
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·3 min
Deep Dive into the Kimi-K3 Technical Report: A Comprehensive Analysis of Architecture, Long-Context Processing, and Reasoning Capabilities
Deep dive into Moonshot AI's Kimi-K3 technical report, analyzing its long-context processing, MoE architecture, reasoning improvements, and its position in global AI competition.
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·4 min
Gemini 3.5 Checkpoint Leaked: Intermediate Version Reportedly Outperforms Opus 5 in Testing
Reddit leaks suggest a Google Gemini 3.5 intermediate checkpoint outperformed Claude Opus 5 max thinking in testing. We analyze what checkpoints mean, benchmark credibility, and the LLM competition landscape.
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·5 min
30+ Free AI & Machine Learning Classic Textbooks: All in One GitHub Repository
Awesome Free AI Books is an open-source repo with 30+ legally free AI & ML classic textbooks covering deep learning, reinforcement learning, NLP, LLMs, and more — all linking to official sources with weekly automated link checks.
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·5 min
Liang Wenfeng's 4-Hour Internal Talk: DeepSeek's Philosophy of Restraint and Its Path to AGI
DeepSeek founder Liang Wenfeng shares his views on open source, pricing, computing power, and the five-stage roadmap to AGI in a 4-hour internal investor talk.
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·3 min
From Word Vectors to Large Language Models: The Complete Evolution of AI 2.0 Technology
From word vectors and embeddings to RNNs, BERT, Transformers, and ChatGPT — a complete guide to the technical evolution of large language models and the AI 2.0 era.
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From Math to AI Research Engineer: A D…
·2 min
From Math to AI Research Engineer: A Deep Dive into the Viral GitHub Learning Roadmap
A GitHub project called maths-cs-ai-compendium surpassed 6,000 Stars with a roadmap for becoming an AI/ML Research Engineer. Here's what makes it worth following.
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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
AI Is Conquering World-Class Math Conjectures — Will Mathematicians Become "Curators"?
AI is cracking world-class math conjectures at scale — from IMO gold medals to the Langlands Program. Terence Tao says math has entered a "proof abundance" era, but AI can't judge research significance. The mathematician's edge is shifting from proving to curating.
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·3 min
OpenAI Executive Fallout and the Truth About AI Salaries: Key Industry Signals Every Practitioner Should Know
OpenAI CFO split with Sam Altman threatens IPO. This deep dive exposes AI salary realities, tool selection pitfalls, Fed macro risks, and signals that AI is entering a zero-sum era.
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·3 min
AI/ML Students Lost in Job Search? A Deep Comparison of Four Career Paths and How to Choose
AI/ML students unsure which career path to pursue? Compare AI engineering, SDE, PM, and UI/UX in depth — with honest entry barriers and a practical self-assessment framework.
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Neural Networks in SQL: A Geek Experim…
·3 min
Neural Networks in SQL: A Geek Experiment That Reveals Deep Learning's Core Principles
A developer implemented a neural network in pure SQL, including matrix multiplication, activation functions, and backpropagation. A deep dive into the technical implementation, challenges, and what it reveals about deep learning's core principles.
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·3 min
Perplexity AI Deep Dive: The Perfect Fusion of Search Engine and AI Q&A
Deep dive into Perplexity AI: real-time web search + multi-model AI, transparent citations, Focus Modes, PDF chat, and collaborative Collections. Can it replace Google and ChatGPT?
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·3 min
Can GPT-5.6 Prove a 50-Year Graph Theory Conjecture? The Boundaries and Verification of AI Mathematical Reasoning
GPT-5.6 Soul Ultra claims to prove the 50-year-old Cycle Double Cover Conjecture in under an hour using 64 parallel agents. We examine the technical path, missing peer review, and formal verification gaps.
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