000 01519nam a22002777i 4500
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020 _a9789391030421
040 _aEG-GaU‬‬
_cEG-GaU‬‬
_dEG-GaU‬‬
_erda
082 _223
_a006.3
_bk.a.p.
100 _aKumar, Alok,
_eauthor.
_960428
245 1 0 _aPractical full‑stack machine learning :
_bA guide to build reliable, reusable, and production‑ready full‑stack ML solutions /
_cAlok Kumar.
250 _a 1st edition.
264 1 _aNew Delhi :
_bBPB Publications,
_c2021.
300 _a422 pages :
_billustrations ;
_c20 cm.
336 _2rdacontent
_atext
_btxt
337 _2rdamedia
_aunmediated
_bn
338 _2rdacarrier
_avolume
_bnc
504 _aIncludes bibliographical references.
505 _a1. Organizing Your Data Science Project ‡ 2. Preparing Your Data Structure ‡ 3. Building Your ML Architecture ‡ 4. Bye‑Bye Scheduler, Welcome Airflow ‡ 5. Organizing Your Data Science Project Structure ‡ 6. Feature Store for ML ‡ 7. Serving ML as API.
520 _aPractical guide introducing production‑ready full‑stack ML pipelines using Python. Covers feature engineering, dataops, Airflow, Dask, MLflow, SageMaker, FastAPI, and scalable API deployment.:contentReference[oaicite:1]{index=1}
650 _aMachine learning
_xImplementation.
_960427
650 _aPython (Computer program language)
_xProgramming.
_960429
942 _2ddc
_cBK
999 _c11065
_d11065