∇θ J(θ) p(y|x) Σ wᵢxᵢ argmin L(θ) O(n log n) λ = 0.001 y = Wx + b ReLU(x) softmax(z) π(a|s) Q(s,a) H(X) = -Σp(x)log p(x) f(x) = max(0, x) μ ± σ

$ python train.py --epochs 100 $ git commit -m "improve model stability" $ ssh yunda@server $ docker compose up --build $ uvicorn app:app --reload $ SELECT * FROM projects; $ torch.cuda.is_available() $ sklearn.model_selection $ API_KEY=******** $ pytest -q

∇θ J(θ) argmin L(θ) softmax(z) Q(s,a) π(a|s) y = Wx + b λ = 0.001 O(n log n) P(A|B) f(x) = x² + b ReLU(x) σ(x)

python train.py git commit -m "ship" ssh yunda@server SELECT * FROM jobs; docker compose up loss.backward() model.eval() import torch pip install -r requirements.txt API_KEY=********

Σ xᵢwᵢ ∫ f(x) dx μ, σ, θ ||x - y||² d/dx z = (x - μ) / σ Attention(Q,K,V) F1 = 2PR / (P + R) AUC ROC p(x|θ)

AVAILABLE FOR OPPORTUNITIES

Yunda Qiu

AI Engineer · Data Analyst · Python Developer

Building practical machine learning systems, data products, and Python tools.

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Open to AI Engineer / Data Analyst / Python Developer roles

profile.sh

$ whoami
> yunda_qiu

$ stack --top
> Python / ML / Analytics / APIs

// about

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Practical projects related to machine learning, analytics, computer vision, time-series, robotics, and engineering delivery.

// tech stack

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More than these. Learning daily, evolving always.

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Feel free to reach out for AI engineering, data analysis, Python development, IT sopport, or related opportunities.