000			01912nam a2200205Ia 4500
003			NULRC
005			20250520102954.0
008			250520s9999 xx 000 0 und d
020			_a9781798130216
040			_cNULRC
050			_aQ 325.5 .B53 2019
100			_aBlack, Eddie _eauthor
245		0	_aMachine learning A-Z : _bintroduction to AI digital brains of the future / _cEddie Black
260			_a[Place of publication not identifed] : _bIndependently published, _cc2019
300			_a51 pages ; _c28 cm.
505			_a1. Part 1-Data Processing -- 2. Part 2.-Regression -- 3. Part 3.-Classification -- 4. Part 4. Clustering -- 5. Part 5. Association Rule Learning -- 6. Part 6. Reinforcement Learning -- 7. Part 7. Natural Language Processing -- 8. Part 8. Deep Learning -- 9. Part 9. Dimensionality Reduction -- 10. Part 10. Model Selection & Boosting.
520			_aNeural Network, Machine Learning, Deep Learning, Deep Neural Network, Artificial Neural Network, Recurrent/Convolutional/MLP.It all sounds very fancy but what does it really mean? How do I get a good basic understanding of these concepts? These questions i asked myself when i was new to the subject of Deep Learning. Everything seemed so complicated to me and as I was a complete beginner all the information I could find seemed to explain advanced mathematical equations that could as well have been written in Hieroglyphs as far as i was concerned. As I progressively learned how things related to each other, and how to understand the terminology used in the subject I realised the explanations could be simplified a lot to be much easier to grasp, just with some overall structure that anyone could understand. The goal of this book is to clarify some uncertainties and give you a solid foundation to be able to dig deeper into this incredibly exciting area of computer science.
650			_aDATA PROCESSING
942			_2lcc _cBK
999			_c20226 _d20226