The Complete Recurrent Neural Network with Python Course

The Complete Recurrent Neural Network with Python Course, available at $39.99, has an average rating of 4.55, with 39 lectures, based on 39 reviews, and has 149 subscribers.

You will learn about Text analysis Image analysis Embedding layers Word embedding Long short-term memory models Sequence-to-vector models Vector-to-sequence models Bi-directional LSTM Sequence-to-sequence models Transforming words into feature vectors frequency-inverse document frequency Cleaning text data Processing documents into tokens Topic modeling with latent Dirichlet allocation Decomposing text documents with LDA Autoencoder Numpy Pandas Tensorflow Sentiment Analysis Matplotlib out-of-core learning This course is ideal for individuals who are Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Anyone passionate about Artificial Intelligence or Data Scientists who want to take their AI Skills to the next level It is particularly useful for Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Anyone passionate about Artificial Intelligence or Data Scientists who want to take their AI Skills to the next level.

Enroll now: The Complete Recurrent Neural Network with Python Course

Summary

Title: The Complete Recurrent Neural Network with Python Course

Price: $39.99

Average Rating: 4.55

Number of Lectures: 39

Number of Published Lectures: 39

Number of Curriculum Items: 40

Number of Published Curriculum Objects: 40

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Text analysis

Image analysis

Embedding layers

Word embedding

Long short-term memory models

Sequence-to-vector models

Vector-to-sequence models

Bi-directional LSTM

Sequence-to-sequence models

Transforming words into feature vectors

frequency-inverse document frequency

Cleaning text data

Processing documents into tokens

Topic modeling with latent Dirichlet allocation

Decomposing text documents with LDA

Autoencoder

Numpy

Pandas

Tensorflow

Sentiment Analysis

Matplotlib

out-of-core learning

Who Should Attend

Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence

Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence

Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.

Anyone passionate about Artificial Intelligence

Data Scientists who want to take their AI Skills to the next level

Target Audiences

Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence

Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence

Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.

Anyone passionate about Artificial Intelligence

Data Scientists who want to take their AI Skills to the next level

Interested in the field of Machine Learning, Deep Learning, and Artificial Intelligence? Then this course is for you!

This course has been designed by a software engineer. I hope with the experience and knowledge I did gain throughout the years, I can share my knowledge and help you learn complex theories, algorithms, and coding libraries in a simple way.

I will walk you step-by-step into Deep Learning. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Recurrent Neural Network. Throughout the brand new version of the course, we cover tons of tools and technologies including:

Deep Learning.

Google Colab

Keras.

Matplotlib.

Splitting Data into Training Set and Test Set.

Training Neural Network.

Model building.

Analyzing Results.

Model compilation.

Make a Prediction.

Testing Accuracy.

Confusion Matrix.

ROC Curve.

Text analysis.

Image analysis.

Embedding layers.

Word embedding.

Long short-term memory (LSTM) models.

Sequence-to-vector models.

Vector-to-sequence models.

Bi-directional LSTM.

Sequence-to-sequence models.

Transforming words into feature vectors.

frequency-inverse document frequency.

Cleaning text data.

Processing documents into tokens.

Topic modelling with latent Dirichlet allocation

Decomposing text documents with LDA.

Autoencoder.

Numpy.

Pandas.

Tensorflow.

Sentiment Analysis.

Matplotlib.

out-of-core learning.

Bi-directional LSTM.

Moreover, the course is packed with practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models. There are several projects for you to practice and build up your knowledge. These projects are listed below:

Bitcoin Prediction

Stock Price Prediction

Movie Review sentiment

IMDB Project.

MNIST Project.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course structure

Lecture 2: How to make the most out of this course

Lecture 3: Explanation of tools in this course

Lecture 4: What is the prerequisite of this course

Chapter 2: Recurrent Neural Network (fundamental)

Lecture 1: Introduction to Recurrent Neural Network (RNN)

Lecture 2: Introduction to Long short term Memory (LSTM)

Lecture 3: Bitcoin prediction Part 1

Lecture 4: Bitcoin prediction Part 2

Lecture 5: Bitcoin prediction Final Part

Chapter 3: Stock price Prediction

Lecture 1: Apple Stock Price prediction with 50 neurons Part 1

Lecture 2: Apple Stock Price prediction with 50 neurons Part 2

Lecture 3: Apple Stock Price prediction with 100 neurons

Lecture 4: Microsofts Stock Price Prediction with Added Regularization

Lecture 5: Microsofts Stock Price Prediction with 100 neurons

Chapter 4: Sentiment Analysis

Lecture 1: Introduction to Natural Language Processing (NLP) and sentiment analysis

Lecture 2: Movie sentiment analysis project Part 1

Lecture 3: Movie sentiment analysis project Part 2

Lecture 4: Movie sentiment analysis project Part 3

Lecture 5: Movie sentiment analysis project Part 4

Lecture 6: Movie sentiment analysis project Part 5

Lecture 7: Movie sentiment analysis project Part 6

Lecture 8: Movie sentiment analysis project Part 7

Lecture 9: Movie sentiment analysis project Part 8

Lecture 10: Movie sentiment analysis project Part 9

Lecture 11: Movie sentiment analysis project Part 10

Lecture 12: Movie sentiment analysis project Part 11

Lecture 13: Movie sentiment analysis project Final Part

Chapter 5: IMDB Project

Lecture 1: Introduction to simple RNN and embedding layer

Lecture 2: IMDB Project Part 1

Lecture 3: IMDB Project Part 2

Lecture 4: IMDB Project Part 3

Lecture 5: IMDB Project Part 4

Lecture 6: IMDB Project Final Part

Lecture 7: MNIST Project Part 1

Lecture 8: MNIST Project Part 2

Lecture 9: MNIST Project Part 3

Lecture 10: MNIST Project Part 4

Lecture 11: MNIST Project Final Part

Chapter 6: Thank you

Lecture 1: Thank you

Instructors

Hoang Quy La
Electrical Engineer

Rating Distribution

1 stars: 4 votes

2 stars: 1 votes

3 stars: 2 votes

4 stars: 1 votes

5 stars: 31 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!