| 000 | 01583nam a22002777i 4500 | ||
|---|---|---|---|
| 005 | 20250915110229.0 | ||
| 008 | 250722s2021 ii ao||fr|||| 00| 0 eng d | ||
| 020 | _a9789388511971 | ||
| 040 |
_aEG-GaU _cEG-GaU _dEG-GaU _erda |
||
| 082 | 0 | 4 |
_223 _a006.31015195 _bs.h.s. |
| 100 | 1 |
_aSingh, Himanshu, _eauthor. _960444 |
|
| 245 | 1 | 0 |
_aStatistics for machine learning : _bimplement statistical methods used in machine learning using Python / _cHimanshu Singh. |
| 250 | _a 1st edition. | ||
| 264 |
_aNew Delhi : _bBPB Publications, _c2021. |
||
| 300 |
_a278 pages : _billustrations ; _c24 cm. |
||
| 336 |
_2rdacontent _atext _btxt |
||
| 337 |
_2rdamedia _aunmediated _bn |
||
| 338 |
_2rdacarrier _avolume _bnc |
||
| 504 | _aIncludes bibliographical references. | ||
| 505 | _aChapter 1: Introduction to Statistics ‡ 2: Descriptive Statistics ‡ 3: Probability ‡ 4: Random Variables ‡ 5: Parameter Estimation ‡ 6: Hypothesis Testing ‡ 7: Analysis of Variance ‡ 8: Regression ‡ 9: Non‑Parametric Statistics ‡ 10: Data Analysis Using Python ‡ 11: Introduction to Machine Learning. | ||
| 520 | _aA practical guide combining statistical theory and Python applications for machine learning. Covers descriptive stats, probability, hypothesis testing, ANOVA, regression, non-parametric methods, and basic ML concepts with code examples.:contentReference[oaicite:1]{index=1} | ||
| 650 |
_aStatistics _xStudy and teaching. _960445 |
||
| 650 |
_aStatistical programming _960446 |
||
| 942 |
_2ddc _cBK |
||
| 999 |
_c11072 _d11072 |
||