AI4ALL: Natural Language Processing

AI4ALL: Natural Language Processing, available at Free, has an average rating of 3.89, with 10 lectures, based on 9 reviews, and has 2215 subscribers.

You will learn about Explore the foundational building blocks of language problems Learn to use Tensorflow to process languages Learn to build Recurrent Neural Network models to predict sentiment Learn and explore more advanced NLP topics such as LSTM This course is ideal for individuals who are Pre-college level students interested in recurrent neural network models It is particularly useful for Pre-college level students interested in recurrent neural network models.

Enroll now: AI4ALL: Natural Language Processing

Summary

Title: AI4ALL: Natural Language Processing

Price: Free

Average Rating: 3.89

Number of Lectures: 10

Number of Published Lectures: 10

Number of Curriculum Items: 10

Number of Published Curriculum Objects: 10

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Explore the foundational building blocks of language problems
Learn to use Tensorflow to process languages
Learn to build Recurrent Neural Network models to predict sentiment
Learn and explore more advanced NLP topics such as LSTM

Who Should Attend

Pre-college level students interested in recurrent neural network models

Target Audiences

Pre-college level students interested in recurrent neural network models

This course is created to follow up with the AI4ALL initiatives. The course presents coding materials at a pre-college level and introduces a fundamental pipeline for a neural network model. The course is designed for the first-time learners and the audience who only want to get a taste of a machine learning project but still uncertain whether this is the career path. We will not bored you with the unnecessary component and we will directly take you through a list of topics that are fundamental for industry practitioners and researchers to design their customized neural network model. The course follows the previous sequence where we covered Artificial Neural Network models, Convolutional Neural Network models, and Image-to-Image models. This course focuses on some of the most basical tasks in language problems and develop the basic intuition of Recurrent Neural Networks.

This instructor team is lead by Ivy League graduate students and we have had 3+ years coaching high school students. We have seen all the ups and downs. Moreover, we want to share these roadblocks with you. This course is designed for beginner students at pre-college level who just want to have a quick taste of what AI is about and efficiently build a quick Github package to showcase some technical skills. We have other longer courses for more advanced students. However, we welcome anybody to take this course!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Theory of Recurrent Neural Network

Lecture 3: Embedding Layer

Lecture 4: Dropout

Lecture 5: Long Short Term Memory

Lecture 6: IMDB Movie Review Dataset

Lecture 7: Data Processing

Lecture 8: Simple Recurrent Neural Network Models

Lecture 9: LSTM Models Using Tensorflow

Lecture 10: Evaluations and Interpretations

Instructors

Yiqiao Yin
Data Science, Machine Learning, and Artificial Intelligence

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 2 votes
4 stars: 2 votes
5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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