000			01844nam a2200241Ia 4500
003			NULRC
005			20250520103028.0
008			250520s9999 xx 000 0 und d
020			_a9798558098426
040			_cNULRC
050			_aQ 325.5 .T44 2021
100			_aTheobald, Oliver _eauthor
245		0	_aMachine learning for absolute beginners : _ba plain English introduction / _cOliver Theobald
250			_aThird Edition.
260			_a[United States] : _bScatterplot Press, _cc2021
300			_a179 pages : _billustrations ; _c23 cm.
365			_bUSD16
505			_aPreface -- What is Machine Learning ? -- Machine Learning Categories -- The Machine Learning Toolbox -- Data Scrubbing Setting up your data -- Linear Regression -- Logistic Regression -- k-Nearest -- k-Means Clustering -- Bias & Variance -- Support Vector Machines -- Artificial Neural Networks -- Decision Trees -- Ensemble Modeling -- Development Environment -- Building a Model in Python -- Model Optimization -- Next Steps -- Thank You -- Bug Bounty -- Further Resources -- Appendix: Introduction to Python.
520			_aMachine Learning for Absolute Beginners has been written and designed for absolute beginners. This means plain English explanations and no coding experience required. Where core algorithms are introduced, clear explanations and visual examples are added to make it easy and engaging to follow along at home. This title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing specific algorithms applied in machine learning, including their pros and cons. At the end of the book, I share insights and advice on further learning and careers in this space
650			_aMACHINE LEARNING
700			_aPedersen, Jeremy _eeditor
942			_2lcc _cBK
999			_c21730 _d21730