Artificial Intelligence And Machine Learning | Pradeep Singh, Tapan K Gandhi And Balasubramanian Raman

About The Book / OverviewThis Book Is Designed To Introduce Beginners To The Foundational Concepts And Techniques That Underpin Ai, Focusing On Key Concepts Of Artificial Intelligence From Basic To Advanced. The Aim Is To Provide A Comprehensive Guide That Bridges Theory And Practice, Empowering Readers To Harness The Power Of Data To Build Intelligent Solutions.Structured To Facilitate A Gradual And InDepth Understanding, This Book Takes Readers On A Journey Through The Essential Aspects Of Artificial Intelligence, Machine Learning, And Data Science, Along With Important Concepts Such As Reinforcement Learning, Neural Networks And Deep Learning, Natural Language Processing (Nlp), And Advanced Machine Learning Techniques.To Enrich The Learning Experience, Practical Examples And Exercises Are Included In Every Chapter. Additionally, Future Trends In Ai Are Explored, Encouraging Continuous Curiosity And Exploration Of New Advancements In This Dynamic Field. Salient Features Comprehensive Textbook Covering Artificial Intelligence (Ai) And Machine Learning (Ml). Aligned With The Syllabi Of Universities Across India Where Ai And Ml Are Combined Subjects. Emphasis On HandsOn Learning Through Code Snippets, Practical Examples, And RealWorld Case Studies. Inclusion Of The Latest Methodologies, Tools, And Trends In Data Science And Ai. Discusses Related Topics Such As Nlp, Deep Learning, Neural Networks, Data Mining, And Data Warehousing. Web SupplementsInstructor Resources:A Wealth Of Information Is Available Online Through McgrawHillS Connect Platform: Https://Connect.Mheducation.Com Lecture Powerpoint Slides Solution Manual Student Resources:Available At: Www.Mheducation.Co.In Data Sets ChapterWise Test Bank Answer Keys To ChapterEnd Objective Questions Hints To ChapterEnd Numerical Questions Additional ChapterWise Solved Examples Links To Reference Materials Appendices: Linear Algebra; Probability And Statistics; Geometry And Multivariate Calculus Table Of Contents1 Foundations Of Artificial Intelligence 2 Intelligent Agents And Environments 3 Search And Problem Solving 4 Knowledge Representation And Logical Reasoning 5 Probabilistic Reasoning And Uncertainty 6 Machine Learning Basics And Techniques 7 Supervised Learning Techniques 8 Unsupervised Learning Techniques 9 Neural Networks And Deep Learning Reinforcement Learning 11 Advanced Machine Learning Techniques 12 Natural Language Processing (Nlp) 13 Data Mining And Predictive Analysis 14 Data Warehousing And Business Intelligence 15 Ethics In Ai And Future Trends Index