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020 _a9789811686153
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024 7 _a10.1007/978-981-16-8615-3
_2doi
050 4 _aQ334-342
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_223
100 1 _aTeoh, Teik Toe.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aArtificial Intelligence with Python
_h[electronic resource] /
_cby Teik Toe Teoh, Zheng Rong.
250 _a1st ed. 2022.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2022.
300 _aXIV, 336 p. 20 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aMachine Learning: Foundations, Methodologies, and Applications,
_x2730-9916
505 0 _aPart I Python -- 1 About Python -- 2 What’s Python? -- 3 An Introductory Example -- 4 Basic Python -- 5 Intermediate Python -- 6 Advanced Python -- 7 Python for data analysis -- Part II Artificial Intelligence Basics -- 8 Introduction to artificial intelligence -- 9 Data wrangling -- 10 Regression -- 11 Classification -- 12 Clustering -- 13 Association Rules -- Part III Artificial Intelligence -- Implementations -- 14 Text Mining -- 15 Image Processing -- 16 Convolutional Neural Networks -- 17 Chatbot, Speech and NLP -- 18 Deep Convolutional Generative Adversarial Network -- 19 Neural style transfer -- 20 Reinforcement learning -- 21 References.
520 _aEntering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon’s Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence. This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjectsin deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
650 0 _aArtificial intelligence.
650 0 _aMachine learning.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aPython (Computer program language).
650 0 _aProgramming languages (Electronic computers).
650 1 4 _aArtificial Intelligence.
650 2 4 _aMachine Learning.
650 2 4 _aData Science.
650 2 4 _aPython.
650 2 4 _aProgramming Language.
700 1 _aRong, Zheng.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811686146
776 0 8 _iPrinted edition:
_z9789811686160
776 0 8 _iPrinted edition:
_z9789811693229
830 0 _aMachine Learning: Foundations, Methodologies, and Applications,
_x2730-9916
856 4 0 _uhttps://doi.org/10.1007/978-981-16-8615-3
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c185710
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