Packt | Hands-On Artificial Intelligence for Small Businesses [FCO]
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Files
| 0101.The Course Overview.mp4 | 43.1 MB | ||
| 0102.What Can AI Do for Businesses.mp4 | 31.9 MB | ||
| 0103.Set Up and Installation – Anaconda and PyTorch.mp4 | 9.2 MB | ||
| 0104.Notebooks and Debugging.mp4 | 9.4 MB | ||
| 0105.Working with Lambdas and Functional Programming Tools.mp4 | 21.7 MB | ||
| 0106.Understanding NumPy and Matplotlib.mp4 | 33.1 MB | ||
| 0201.Classification versus Regression.mp4 | 26.8 MB | ||
| 0202.Training, Testing, and Validation.mp4 | 25.9 MB | ||
| 0203.Boosting and Ensembles.mp4 | 18.8 MB | ||
| 0204.Small Data and Cross Validation.mp4 | 6.3 MB | ||
| 0205.Building Artificial Neural Networks.mp4 | 43.9 MB | ||
| 0301.Understanding Unsupervised Learning.mp4 | 25.2 MB | ||
| 0302.Using Bayesian Inference.mp4 | 5.6 MB | ||
| 0303.Expectation Maximization.mp4 | 20 MB | ||
| 0304.Notions of Distance.mp4 | 28.1 MB | ||
| 0305.Hierarchical Clustering Methods.mp4 | 10.9 MB | ||
| 0401.Understanding Semi-Supervised Learning.mp4 | 11.8 MB | ||
| 0402.Nearest Neighbor Search and Collaborative Filtering.mp4 | 28.8 MB | ||
| 0403.Building a Recommendation Engine.mp4 | 8.4 MB | ||
| 0404.Extracting Features from Natural Language.mp4 | 13.9 MB | ||
| 0405.Recommendation Objectives and Clustering.mp4 | 23.6 MB | ||
| 0406.Active Learning.mp4 | 16.1 MB | ||
| 0501.Understanding Reinforcement Learning.mp4 | 15.6 MB | ||
| 0502.Continual AB Testing.mp4 | 38.2 MB | ||
| 0503.Infinite AB Testing.mp4 | 22.6 MB | ||
| 0504.Using Context.mp4 | 124.5 MB | ||
| 0505.Learning Across Time.mp4 | 92.4 MB | ||
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| How you can help Team-FTU.txt | 204.8 B | ||
| exercise_files.zip | 82.5 KB | ||
| ▲ 34 total files | |||
Description
By : Sam Saarinen
Released : 29 Apr 2019 (New Release!)
Torrent Contains : 34 Files, 7 Folders
Course Source : https://www.packtpub.com/big-data-and-business-intelligence/hands-artificial-intelligence-small-businesses-video
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Video Details
ISBN 9781788391863
Course Length 4 hours 31 minutes
Table of Contents
• Getting Started with Artificial Intelligence with Python
• Predicting Sales with Supervised Learning
• Understanding Your Customer Base Using Unsupervised Learning
• Product Recommendations Using Semi-Supervised Learning
• Optimizing Page Layouts and Advertisements Using Reinforcement Learning
Learn
• Build neural networks for Business solutions
• Understand AI and different areas of application in business to manage workflow, optimise operations & predict 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, etc. Recently, small businesses have been leveraging AI to scale up and be more efficient. This course is your stepping stone to mastering the power of AI for your own business.
This course will teach you to approach AI from a leader’s perspective using practical, data-driven methods to identify and quantify business opportunities. 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 and innovate the services of any business using the power of AI.
The code bundle for this video course is available at - https://github.com/PacktPublishing/Hands-on-Artificial-Intelligence-for-Small-Businesses
Style and Approach
This course adopts a hands-on approach to teach you the skills required to develop Artificial Intelligence models for common processes in a small business.
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 intelligence tasks.
• Adapt prewritten example code to your own datasets and challenges.
Author
Sam Saarinen
Sam Saarinen is is an artificial intelligence researcher with a graduate degree from Brown University. He also has a passion for teaching and plans to use AI to improve education worldwide. When he’s not making video games, freestyle rapping, or telling bad jokes – and even when he is – he enjoys spending time with his wife. Sam’s website and a partial list of projects can be found here: sam-saarinen.github.io
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