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Tag: python

after-workhkpcaifinancepython

HKPC AI Foundations for Finance Professionals (Oct 2026) vs after-work Python

HKPC Academy “AI Foundations for Finance Professionals”: Wed 7 Oct 2026, 14:30–17:30, 3h, Cantonese, HKPC Building; intro AI/GenAI for finance workflows, no programming required; ~HKD 1500 (early-bird ~1350 by 23 Sep). Calm contrast vs SoloQuant after-work short Python lessons. Not CEF/Quant-Macro. Not investment advice.

pythonvllm

llm

inference

after-work

vLLM 0.29 after work: Model Runner V2 default

vLLM 0.29.0 (~9 Sep 2026): Model Runner V2 default for all models—CUDA graph memory profiling, batch-sharded sampling (logits mem ~1/TP). MRV1 remains for some ROCm/unsupported features. Deprecated architectures removed; prefer vllm serve. Not transformers-5-17 Hub. Not investment advice.

pythonacceleratefsdp2pytorchafter-work

Accelerate 1.15 after work: FSDP2 activation memory knobs

Accelerate v1.15.0 (9 Sep 2026): FSDP2 activation checkpointing wraps the matched transformer layer (not each child); new fsdp_activation_checkpointing_offload to pinned CPU; tied-embedding fix on torch>=2.13; DTensor grad clip / prepare_model. Hook is Accelerate. Not investment advice.

pythonwandbmlopsexperiment-trackingafter-work

wandb 0.30 after work: breaking API cleanup for experiment trackers

wandb 0.30.0 (9 Sep 2026): InternalApi/PublicApi aliases and internal modules removed—use wandb.Api(); legacy wandb sync options gone; deprecations for wandb.api / ensure_configured / sandbox. Python>=3.10, protobuf>=5. Not Aim CVE or MLflow pickle. Not investment advice.

pythonsqlpolarsduckdbafter-work

Top 5 Python SQL-on-DataFrame tools for after-work learners

Map for SQL-on-DataFrame after work: Polars SQL, SQLGlot, DuckDB, SQLFrame, Ibis. Anchored on Polars 1.44.2 + SQLGlot 30.18 freshness—not DuckDB 2.0 / Polars Iceberg / Polars 2.0 RC retreads. Educational only. Not investment advice.

after-workconferencealgo-tradingpythoncareer

QuantInsti Annual Algo Trading Conference 2026 vs after-work short lessons

Free QuantInsti Annual Algo Trading Conference 2026: Thu 24 Sep 2026 from 6:00 PM IST (8:30 PM SGT)—~75m agentic AI workshop, ~30m HFT fireside, ~60m AI careers panel. Calm contrast with SoloQuant after-work short lessons. Not EPAT/CQF. Not investment advice.

pythonarcticdbarrowtime-seriesafter-work

ArcticDB 6.25 after work: arrow string output formats

ArcticDB 6.25.0 (9 Sep 2026) adds arrow-backed string dtype read/write plus arrow_string_format_default / per_column (LARGE_STRING, SMALL_STRING, CATEGORICAL) for PYARROW/POLARS reads. String-heavy market/TS stores. Not a pyarrow-25 or pandas-3 rewrite. Not investment advice.

pythonsklearncategory-encodersfeature-engineeringafter-work

category-encoders 2.11 after work: MultiHotEncoder + CountTargetEncoder

category-encoders ≥2.11.1 adds MultiHotEncoder (delimiter multi-label cells → binary columns) and CountTargetEncoder (smoothed log-odds target encoding). Fit supervised encoders inside CV folds. Not a data-validation Top5 retread. Not investment advice.

pythontransformershuggingfaceasrafter-work

Transformers 5.17 after work: HYV4, VibeVoice, NeoMME, Fun-ASR, KimiLinear, Canary

Hugging Face Transformers v5.17.0 (9 Sep 2026) adds HYV4/Hy4-Preview MoE, VibeVoice, NeoMME + Retriever, Fun-ASR-Nano, KimiLinear (KDA), and NVIDIA Canary-1B-v2. After-work model checklist—not a CVE post. Not investment advice.

pythonllmragevaluationafter-work

Top 5 Python LLM/RAG evaluation libraries after work

After-work map: ① DeepEval ② Phoenix (Arize) ③ TruLens ④ Ragas ⑤ Giskard — usefulness angles for LLM/RAG eval. Cite official docs/GitHub/PyPI. Educational only; not fake search metrics; not investment advice.

pythoncqfquanteducationafter-work

CQF (27 Jan 2027 start) vs after-work short lessons

CQF next start 27 Jan 2027; ~6 months online part-time master’s-level quant finance/ML (CQF Institute / Fitch Learning). Calm contrast vs SoloQuant after-work short lessons. CTA only Intro to Python. Not investment advice.

pythonforecastingneuralforecasttimeseriesafter-work

NeuralForecast 3.2 after work: categorical exogenous via embeddings

NeuralForecast v3.2.0 (2026-07-10): categorical exogenous for univariate non-recurrent models via embeddings (cat_exog_list, categorical_cardinalities, cat_emb_dim). Educational after-work note. Not investment advice.

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