Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 40 Minute(s)
Language
English
Taught by
Mousa Al Bateh
Rating
Course Overview
Develop in Java an AI for chat bots, language detection and sentiment analyses for marketing
Have you ever wanted to develop your own AI?
Have you ever visited a website and you were surprised how the chat bot understands your messages?
Have you ever wondered how Google detects the language you're typing in?
Have you ever wondered how are some services able to analyze and understand the sentiment in a text?
AI is currently one of the hottest trends and businesses now strive for hiring AI specialists to develop and train AI in many areas from basic tasks such as assembly in factories to advanced applications such as weather, marketing and other disciplines. In general, AI technology is evolving and is eventually going to be used to help build structures on other planets.
This course will cover the basics of how to use Apache's OpenNLP to implement the above and also simplify things so you will realize that developing your own AI is not as complicated as it seems.
While developing AI is popular in Python, Java is still being actually used by many businesses for developing AI as much as in Python. This course has been specially made for those who are too lazy to learn Python and would like to utilize their existing skill in Java and harness all the strengths and benefits of Java and love optimization and high performance.
Warning:
This course does not cover data science at the moment since the course is currently focused on implementation rather than theory.
Course Content
- 6 section(s)
- 20 lecture(s)
- Section 1 Introduction
- Section 2 Natural Language Processing Explanation and Theory
- Section 3 Project Setup
- Section 4 Making a Smart Chat Bot
- Section 5 Language Detection Using Apache's OpenNLP
- Section 6 Sentiment Analyzer
What You’ll Learn
- Understand how Apache OpenNLP works
- AI driven chat bot
- AI driven text sentiment analyzer
- AI driven language detector
Skills covered in this course
Reviews
-
RRoman
The lector speak really slow, on the speed x2, he speak more or less fine, but with the big pauses. The lesson is really show only the lowest level, like a "hello world": - without explanation of "en-lemmatizer.dict", how it was created, and wat does it mean "VB", "DT" and so on. - without explanation, when you configure the neiral network, why do you use "TrainingParameters.CUTOFF_PARAM", and how the initilization chage the result. - how to export/import model that was already trained. It's is a fine course for begginers.
-
PPankaj Saste
Course Content: Course is very good for someone just want to have an introduction to OpenNLP. However it neither covers OpenNLP nor NLP basics in detail. Brief descriptions with detailed resource links should be provided for important concepts of NLP. Course Presentation: Fonts are too small in videos and are very hard to read. Please either zoom or increase the font size. It would help if you explain in brief about the classes being used in code such as Why this class, what are alternatives etc.
-
MMatthew Burnell
It was a good introduction to Apache OpenNLP.
-
DDesmond David
Nice succinct and to the point but marred by some technical problems. The audio needs normalizing to reduce sibilance (high pitch spikes in audio when speaking S or Sh words). At times the audio breaks, making understanding some parts difficult. Also, despite sentiment analysis being advertised, it's not currently in the course after one year (at the time of writing this review) since the last update. Though I am looking forward to more course content.
