Data Science with Artificial Intelligence, Machine Learning and Deep Learning
The Present book takes a student from "unknown to known" and " simple to complex" principles of Data Science. This book is user-friendly, thought provoking and stimulating. It helps in clearing the cobwebs of the mind and the subject. The style used is lucid and un-adulterated. What stands out is the stark simplicity with which the ideas have been portrayed.
A good book should teach the customary and effective ways to structure your code in such a way that data engineering is not havoc. Python is an object-oriented programming language that is used in this book .
The book is divided in to 4 Units:-
Unit-1 has 15 chapters on Artificial Intelligence.
Unit-2 has 7 chapters that explain Machine Learning and IOT.
Unit-3 has 10 chapters each focusing on DEEP Learning.
Unit-4 has 1 chapter that explain Data Sciences.
- Unit-I : Artificial Intelligence
- Introduction to AI
- Intelligent Agents
- AI Approaches
- Uninformed Search Strategies
- Informed Search
- Games Solving
- Constraint Satisfaction Problems
- Knowledge Representation
- AI Retrospectives
- Representation Knowledge
- Planning & Learning
- Uncertain Knowledge & Reasoning
- NLP
- Expert Systems
- ANNS
- Unit-II:- Machine Learning
- Introduction to ML
- Types of Learning
- Classification Families
- Learning Algorithms
- Unsupervised Learning and their Algorithms
- Reinforcement Learning and Control
- loT and ML
- UNIT-lll :- Deep Learning
- The Neural Network (DL)
- Machine Learning Retrospective
- Deep feed forward Networks
- Deep Learning Optimization
- CNNs
- Sequence Analysis
- Practical Deep Learning
- Applications of Deep Learning
- Deep Learning Survey
- Roses are Red, Violets are Blue, Deep Learning Can Recognize Objects for you.
- UIT lV: Data Science
- Data Science
- Glossary
- Model Question Papers
- References
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