Demystifying Artificial intelligence

Simplified AI and Machine Learning concepts for Everyone (English Edition)

Prashant Kikani

• Verlag: BPB Publications
• Jahr: 2021
• ISBN:
  9789389898705
• Thema: Informatik
• Thema: Computer Vision & Mustererkennung

Learn AI & Machine Learning from the first principles.Key Features? Explore how different industries are using AI and ML for diverse use-cases.? Learn core concepts of Data Science, Machine Learning, Deep Learning and NLP in an easy and intuitive manner.? Cutting-edge coverage on use of ML for business products and services.? Explore how different companies are monetizing AI and ML technologies.? Learn how you can start your own journey in the AI field from scratch.DescriptionAI and machine learning (ML) are probably the most fascinating technologies of the 21st century. AI is literally in every industry now. From medical to climate change, education to sport, finance to entertainment, AI is disrupting every industry as we know.So, the basic knowledge of AI/ML becomes mandatory for everyone. This book is your first step to start the journey in this field. Along with basic concepts of fields, like machine learning, deep learning and NLP, we will also explore how big companies are using these technologies to deliver greater user experience and earning millions of dollars in profit.Also, we will see how the owners of small- or medium-sized businesses can leverage and integrate these technologies with their products and services. Leveraging AI and ML can become that competitive moat which can differentiate the product from others.In this book, you will learn the root concepts of AI/ML and how these inanimate machines can actually become smarter than the humans at a few tasks, and how companies are using AI and how you can leverage AI to earn profits.What you will learn? Core concepts of data science, machine learning, deep learning and NLP in simple and intuitive words.? How you can leverage and integrate AI technologies in your business to differentiate your product in the market.? The limitations of traditional non-tech businesses and how AI can bridge those gaps to increase revenues and decrease costs.? How AI can help companies in launching new products, improving existing ones and automating mundane processes.? Explore how big tech companies are using AI to automate different tasks and providing unique product experiences to their users.Who this book is forThis book is for anyone who is curious about this fascinating technology and how it really works at its core. It is also beneficial to those who want to start their career in AI/ ML.Table of Contents1. Introduction2. Going deeper in ML concepts3. Business perspective of AI4. How to get started and pitfalls to avoidAbout the AuthorsPrashant Kikani is an experienced data scientist, who ranks in the top 1% worldwide in competitions and kernels on Kaggle which is the world's largest community and platform for data science and machine learning.As part of his day-to-day work, he is working on solving some of the hardest problems for the human kind, like language translation using state-of-the-art deep learning-based NLP models and infusion of knowledge graphs in NLP models. He is one of the youngest students to achieve the Master title on the Kaggle kernel platform. Also, he has worked on other deep learning sub-fields like computer vision via Kaggle competitions.His interests lie in AI/ML and deep learning, and teaching others what he has learned in a very simple and intuitive manner. This book is part of his interest to share his knowledge in the simplest possible manner with everyone so that everyone they can learn about this fascinating technology called AI!Prashant's ultimate goal is to make a positive impact on millions of people's daily lives and to always be optimistic about the future. To achieve these goals, he has started multiple initiatives. You can know more about him at prashantkikani.com.Blog links: http://prashantkikani.comLinkedIn Profile: https://www.linkedin.com/in/prashant-kikani/

Inhaltsverzeichnis

• Cover Page
• Title Page
• Copyright Page
• Dedication Page
• About the Author
• About the Reviewers
• Acknowledgement
• Preface
• Errata
• Table of Contents
• 1. Introduction
• 2. Going Deeper into ML Concepts
• 3. Business Perspective of AI
• 4. How to Get Started, and Pitfalls to Avoid in AI
• References
• Index