Hands-On Artificial Intelligence for Small Businesses [Video]

More Information
Learn
  • Build neural networks for business solutions
  • Understand AI and its different areas of application to business for managing workflows, optimizing operations, and predicting trends
  • Create machine learning models using supervised and unsupervised machine learning techniques
  • Build smart systems to analyze data for enhanced customer experience
  • Optimize machine learning models for better performance and accuracy
  • Design intelligent agents to solve real-world problems
About

Artificial Intelligence has become an important and integral part of many industries, revolutionizing sectors such as banking, medicine, transportation, and more. Recently, SMEs have been leveraging AI to scale up and become more efficient and competitive. This course is your stepping stone to master the power of AI for your own business and help increase its competitive edge to drive growth and market differentiation.

This course will teach you to approach AI from a business leader’s perspective using practical, data-driven methods to identify and quantify business opportunities. Using Python, you will learn to use several varieties of machine learning techniques, improving the capability of your business to deliver better and faster solutions to its customers and clients.

By the end of the course, you will have the skills to improve the services and innovations of your business using the power of AI and key Python tools.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Hands-on-Artificial-Intelligence-for-Small-Businesses

Features
  • Apply AI to predicting sales, understanding your customers, making recommendations, optimizing business and design decisions, and processing user comments
  • Explore widely used Python packages and tools to perform artificial intelligence tasks
  • Adapt pre-written example code to your own datasets and challenges
Course Length 4 hours 31 minutes
ISBN 9781788391863
Date Of Publication 30 Apr 2019