Pubha Mehta
Deep Learning: Unleashing the Power of Artificial Intelligence
Books by Mrs. S. Sangeetha, C. Roopa
"Deep Learning: Unleashing the Power of Artificial Intelligence" is a comprehensive book that takes readers on a journey through the fascinating world of deep learning. With a focus on artificial intelligence (AI), this book explores the transformative potential of deep learning algorithms in various domains. Covering both theory and practical applications, this book provides a solid foundation in deep learning concepts, including neural networks, convolutiona
Genetic Algorithm and Machine learning
Books by Dr. A . Rohini, Preeti Nutipalli, Sreelahari Vallamsetla
The text introduces the theory, operation, and application of genetic algorithms search algorithms based on the mechanics of Machine Learning.
Beyond Artificial Intelligence
Books by Dhananakodi. V, M. Gayathri , Rajakumaran. V
Beyond Artificial Intelligence is a full breadth and depth of the field of artificial intelligence (AI).
Advancements to Machine Learning with Python
Books by Dr. M. Ramasubramanian, Dr. Dasari Madhavi, Dr S Sivasubramanian, Dr. Mohan Mahanty
This book is written to provide a strong foundation in Machine Learning using Python libraries by providing real-life case studies and examples.
Fundamentals of Machine Learning and Its Applications
Books by Dr. N. Gomathi, Dr. C. Chandravathi, Dr. P. Shanthi, Dr. J. Velmurugan
This book is a general introduction to machine learning that can serve as a textbook
for students and researchers in the field. It covers fundamental modern topics in
machine learning while providing the theoretical basis and conceptual tools needed
for the discussion and justification of algorithms. It also describes several key aspects
of the application of these algorithms.
Data Science using Python
Books by Dr. K Abhimanyu Kumar Patro, B.s. Prakash, Ms. M. Gayathri, Dr. Shrikant Zade, S. Mohana Saranya
The Python Data Science Handbook provides a reference to the breadth of computational and statistical methods that are central to data-intensive science, research, and discovery. People with a programming background who want to use Python effectively for data science tasks will learn how to face a variety of problems: e.g., how can I read this data format into my script? How can I manipulate, transform, and clean this data? How can I visualize this type of dat
Introduction to Digital Marketing
Books by Dr. P. V. M. Raju
The Digital Marketing is the comprehensive guide to cracking the digital marketing 'code,' and reaching, engaging, and serving the empowered consumer, this book presents an innovative methodology for successful digital marketing: start with the customer and work backwards. A campaign is only effective as it is reflective of the consumer's wants, needs, preferences and inclinations.
Data Analytics with Python : A Practical Approach
Books by Dr. M. Ramasubramanian, Prof. K. Kiran Kumar
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. This having practical case studies that show you how to solve a broad set of data analysis problems effectively. You will learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. This book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data
Machine Learning: A Reinforcement Learning
Books by Mr. Anil Kumar Chanchal, Amal Joseph, Jeffin Gracewell
The book is exactly what its title claims it to be: lecture notes; nothing more, nothing less! A reader looking for elaborate descriptive expositions of the concepts and tools of machine learning will be disappointed with this book. There are plenty of books out there in the market with different styles of exposition. Some of them give a lot of emphasis on the mathematical theory behind the algorithms. In some others the emphasis is on the verbal descriptions
Introduction to Data Science
Books by Dr Dheva Rajan S, T. Kumaravel, Prof. Valli Madhavi Koti, Amrutha Muralidharan Nair
This is a book on data science with a specific focus on industrial
experience. Data Science is a cross-disciplinary subject involving
hands-on experience and business problem-solving exposures. The
majority of existing introduction books on data science are about
the modeling techniques and the implementation of models using
R or Python. However, many of these books lack the context of the
industrial environment. Moreover, a crucial par
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