000			02226nam a22003737a 4500
003			BT-SaRUSC
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008			250326b |||||||| |||| 00| 0 eng d
020			_a9781098146474 _qpaperback
040			_cBT-SaRUSC
082	0	4	_a006.312 _223 _bVAU
100	1		_aVaughan, Daniel, _eauthor.
245	1	0	_aData science: the hard parts : _btechniques for excelling at data science / _cDaniel Vaughan.
246	3	0	_aTechniques for excelling at data science
250			_aFirst edition.
260			_aBeijing : _bO'Reilly Media, _c2024.
300			_axvi, 237 pages : _billustrations, charts ; _c24 cm
500			_aIncludes index.
520			_aThis hands-on guide offers a set of techniques and best practices that are often missed in conventional data engineering and data science education. A common misconception is that great data scientists are experts in the "bit themes" of the discipline, namely ML and programming. But most of the time, these tools can only take us so far. In reality, it's the nuances within these large themes, and the ability to impact the business, that truly distinguish a top-notch data scientist from an average one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and an exceptional data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries.
541			_aBook Aid International 2024 (Donated by the Bhutan Society of the UK Trust Fund) _d19/3/25 _eD 5297-A21175
650		0	_aElectronic data processing.
650		0	_aBig data.
650		0	_aDatabase management.
650		0	_aData mining.
650		6	_aDonnées volumineuses.
650		6	_aBases de données _xGestion.
650		6	_aExploration de données (Informatique)
650		7	_aBig data _2fast
650		7	_aData mining _2fast
650		7	_aDatabase management _2fast
650		7	_aElectronic data processing _2fast
776	0	8	_iOnline version: _aVaughan, Daniel. _tData science. _bFirst edition. _dSebastopol, [California] : O'Reilly Media, 2023 _z9781098146443 _w(OCoLC)1407278110
942			_2ddc _cBK
999			_c19707 _d19707