by Mark Strefford | Released November 2018 | ISBN: 9781788839532

Build interactive chatbots, facial recognition, headline writers, and more. No AI experience required! About This VideoHands-on examples to simplify your first steps into the world of Artificial Intelligence with PythonGet well-versed with AI concepts and get up-and-running with AI in no timeExample-based approach to developing powerful neural networks quickly using the best machine learning methodsIn DetailPython has surfaced as a dominant language in AI/ML programming because of its simplicity and flexibility. It has great support for open-source libraries such as Scikit-learn and TensorFlow. Built for rookie AI enthusiasts across four realistic projects, this course covers modern techniques that make up the world of Artificial Intelligence. Dive into your first natural language processing project, build a facial recognition system, and build your very own self driving steering code. You will explore the use of neural networks and deep learning, and how you can train and test sets for feature extraction. You'll be introduced to the Keras deep learning library, which you will use to predict taxi journey times, and to the use of natural language processing to find the most relevant articles in Wikipedia.By the end of this video course, you will be confident enough to build your own AI projects with Python, and ready to take on more advanced content as you move on.The code bundle for this video course is available at - https://github.com/PacktPublishing/Learning-Python-Artificial-Intelligence-by-Example Show and hide more

1. Chapter 1 : Using Natural Language Processing with Knowledge Bases
   • The Course Overview 00:05:20
   • Building a Dataset From Wikipedia Content 00:09:55
   • Introducing Topic Modeling 00:06:25
   • Using gensim and NLTK 00:02:48
   • The Code 00:13:13
   • Building a Web Service 00:05:34
2. Chapter 2 : Face Recognition
   • How Does Face Recognition Work? 00:05:20
   • Using OpenCV for Face Recognition 00:03:50
   • AWS Rekognition 00:08:50
   • Recognizing Faces in Video 00:08:22
3. Chapter 3 : Predicting Taxi Journey Times
   • Summary of the Problem 00:03:15
   • Exploring the Data 00:08:59
   • Training the Model 00:09:16
   • Predicting Journey Times 00:03:54
4. Chapter 4 : Predicting the Steering Angles of a Self Driving Car
   • CNNs 00:03:11
   • Environment and Data 00:04:54
   • Training Our Model 00:11:16
   • Inferring Steering Angles 00:04:31
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