by Sam Saarinen | Released April 2019 | ISBN: 9781788391863

Drive your business with faster, smarter solutions and services using the power of artificial intelligenceAbout This VideoApply AI to predicting sales, understanding your customers, making recommendations, optimizing business and design decisions, and processing user commentsExplore widely used Python packages and tools to perform artificial intelligence tasksAdapt pre-written example code to your own datasets and challengesIn DetailArtificial 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.Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/Hands-on-Artificial-Intelligence-for-Small-Businesses. If you require support please email: [email protected] Show and hide more

1. Chapter 1 : Getting Started with Artificial Intelligence with Python
   • The Course Overview 00:06:06
   • What Can AI Do for Businesses? 00:04:17
   • Set Up and Installation - Anaconda and PyTorch 00:05:24
   • Notebooks and Debugging 00:05:25
   • Working with Lambdas and Functional Programming Tools 00:10:31
   • Understanding NumPy and Matplotlib 00:13:44
2. Chapter 2 : Predicting Sales with Supervised Learning
   • Classification versus Regression 00:12:45
   • Training, Testing, and Validation 00:13:10
   • Boosting and Ensembles 00:09:14
   • Small Data and Cross Validation 00:03:24
   • Building Artificial Neural Networks 00:19:49
3. Chapter 3 : Understanding Your Customer Base Using Unsupervised Learning
   • Understanding Unsupervised Learning 00:13:05
   • Using Bayesian Inference 00:03:46
   • Expectation Maximization 00:11:03
   • Notions of Distance 00:11:50
   • Hierarchical Clustering Methods 00:05:36
4. Chapter 4 : Product Recommendations Using Semi-Supervised Learning
   • Understanding Semi-Supervised Learning 00:06:29
   • Nearest Neighbor Search and Collaborative Filtering 00:16:03
   • Building a Recommendation Engine 00:05:21
   • Extracting Features from Natural Language 00:07:58
   • Recommendation Objectives and Clustering 00:15:09
   • Active Learning 00:09:54
5. Chapter 5 : Optimizing Page Layouts and Advertisements Using Reinforcement Learning
   • Understanding Reinforcement Learning 00:09:29
   • Continual A/B Testing 00:18:06
   • Infinite A/B Testing 00:09:00
   • Using Context 00:10:16
   • Learning Across Time 00:14:49
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