CG数据库 >> Learning Python Artificial Intelligence by Example

$125 | Duration: 1h 58m | Video: h264, 1920×1080 | Audio: AAC, 48kHz, 2 Ch | 429 MBGenre: eLearning | Language: English | November 30, 2018Build interactive chatbots, facial recognition, headline writers, and more. No AI experience required!Python 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 –Style and ApproachBuilt for amateur AI enthusiasts and using realistic examples, this course covers modern techniques that make up the world of Artificial Intelligence.

Table of ContentsUSING NATURAL LANGUAGE PROCESSING WITH KNOWLEDGE BASESFACE RECOGNITIONPREDICTING TAXI JOURNEY TIMESPREDICTING THE STEERING ANGLES OF A SELF DRIVING CARWhat You Will LearnCreate your own NLP chatbot using Python AIUse open source, SaaS and custom-built algorithms to identify faces in pictures and videoUnderstand data-mining methods, and how to work with multiple data sets when building a modelHow feature engineering works to get the most value from the dataApply open data and deep learning to predict taxi journey times in New York CityUse convolutional neural networks to determine an appropriate steering angle for a self-driving car


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