Python Machine Learning Projects
Dr. Deepali R Vora, Dr. Gresha S Bhatia
Authors: Dr. Deepali R Vora, Dr. Gresha S Bhatia
Publishing Date: 13th March 2023
Dimension: 7.5*9.25 Inches
Book Type: Paperback
Since the last two decades, there have been many advancements in the field of Machine Learning. If you are new or want a comprehensive understanding of Machine Learning, then this book is for you.
The book starts by explaining how important Machine Learning is today and the technology required to make it work. The book then helps you get familiar with basic concepts that underlie Machine Learning, including basic Python Programming. It explains different types of Machine Learning algorithms and how they can be applied in various domains like Recommendation Systems, Text Analysis and Mining, Image Processing, and Social Media Analytics. Towards the end, the book briefly introduces you to the most popular metaheuristic algorithms for optimization.
By the end of the book, you will develop the skills to use Machine Learning effectively in various application domains.
- Understand the core concepts and algorithms of Machine Learning.
- Get started with your Machine Learning career with this easy-to-understand guide.
- Discover different Machine Learning use cases across different domains.
WHAT YOU WILL LEARN
- Discover various applications of Machine Learning in social media.
- Explore image processing techniques that can be used in Machine Learning.
- Learn how to use text mining to extract valuable insights from text data.
- Learn how to measure the performance of Machine Learning algorithms.
- Get familiar with the optimization algorithms in Machine Learning.
WHO THIS BOOK IS FOR
This book delivers an excellent introduction to Machine Learning for beginners with no prior knowledge of coding, maths, or statistics. It is also helpful for existing and aspiring data professionals, students, and anyone who wishes to expand their Machine Learning knowledge.
- Introduction to ML
- Python Basics for ML
- An Overview of ML Algorithms
- Case Studies and Projects in Machine Learning
- Optimization in ML Algorithms
Dr. Deepali R Vora is a Professor and Head of Computer Science & Engineering at Symbiosis Institute of Technology, Pune, and has completed her Ph.D. in Computer Science and Engineering from Amity University, Mumbai. She has more than 22 years of teaching, research as well as Industrial experience. She has more than 60 research papers published in Journals and Conferences of International and national repute. She has co-authored three books and delivered various talks in Data Science and Machine learning. She has conducted hands-on sessions in Data Science using Python for students and faculty. She was appointed as a Syllabus Revision Committee member with Mumbai University and developed the course content for B.E. (Information Technology) course. She has received grants for conducting research and organizing training courses for faculties. She acts as a technical advisor and reviewer for many International Conferences and Journals. Her blogs on KnowledgeHut have received wide acknowledgment. She has developed a course on “Deep Learning” on the Unschool platform.
Dr. Gresha S Bhatia is the Deputy Head of the Computer Engineering Department at Vivekanand Education Society’s Institute of Technology (VESIT), Mumbai, and has completed her Ph.D. Technology from the University of Mumbai. She has more than 25 years of industry and teaching experience. She has published more than 50 research papers in International Journals, conferences, and national conferences of repute. She has been awarded Microsoft AI for Earth Grant in the year 2019 as well as Minor Research Grant from the University of Mumbai. She has authored a book and has delivered sessions on Machine learning and Social Computing. She has also been a member of the Syllabus Revision Committee of Mumbai University for the undergraduate and postgraduate programs in Engineering. She has also been a technical advisor and reviewer for the number of International Conferences and Journals.