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Overview
Machine Learning Engineer at Meta, Kaggle Grandmaster, and Google Developer Expert writing about applied ML, AI paper reviews, systems, and learning.
News
Beyond Bigger MoE: How Kimi K3 Scales Context, Depth, and Agents
Kimi K3 is a 2.8-trillion-parameter open-weight multimodal MoE model that combines hybrid linear-global attention, selective residual connections across depth, and large-scale agentic reinforcement learning.
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Book Review: Python for Algorithmic Trading Cookbook
A review of the second edition of Python for Algorithmic Trading Cookbook by Jason Strimpel, a 68-recipe book that goes from getting raw data to live execution on the Interactive Brokers API.
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Harness Handbook: The Missing Layer for Editing AI Agents
Harness Handbook proposes a new way to navigate large AI agent codebases by organizing them around behaviors instead of files. The result is better code localization, higher-quality edit plans, and more efficient agent engineering.
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Book Review: Time Series with PyTorch
A review of Time Series with PyTorch, a broad deep-learning-for-forecasting book that teaches from honest evaluation and PyTorch fundamentals through RNNs, transformers, conformal prediction and diffusion, and on into classification, clustering, and anoma
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Starting and iterating on a Kaggle competition in Google Antigravity
I used a Claude Code starter kit and Google Antigravity with Gemini 3.1 to participate in a Kaggle Playground competition. Most of the work was catching the silent bugs and stopping the agent from taking wrong turns.
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