Build your deep learning portfolio: Meditations with LSTM

Build your deep learning portfolio: Meditations with LSTM, available at $19.99, has an average rating of 4.06, with 12 lectures, based on 9 reviews, and has 113 subscribers.

You will learn about Create an LSTM for generating text This course is ideal for individuals who are Deep learning students, who want to build their portfolio It is particularly useful for Deep learning students, who want to build their portfolio.

Enroll now: Build your deep learning portfolio: Meditations with LSTM

Summary

Title: Build your deep learning portfolio: Meditations with LSTM

Price: $19.99

Average Rating: 4.06

Number of Lectures: 12

Number of Published Lectures: 12

Number of Curriculum Items: 12

Number of Published Curriculum Objects: 12

Original Price: €219.99

Quality Status: approved

Status: Live

What You Will Learn

Create an LSTM for generating text

Who Should Attend

Deep learning students, who want to build their portfolio

Target Audiences

Deep learning students, who want to build their portfolio

In this deep learning course I’m going to teach you to create an LSTM model for generating text using Keras with Tensorflow backend. I am using Marcus Aurelius Meditations as my source text, hence the name of the course. This course is best suited for students, who are already familiar with Python and want to build their deep learning portfolio.

Course Curriculum

Chapter 1: Creating the LSTM model for text generation

Lecture 1: Introduction

Lecture 2: Create a plan

Lecture 3: Obtain the data

Lecture 4: Analyze the data

Lecture 5: Clean the data

Lecture 6: Prepare the data

Lecture 7: Create the LSTM model

Lecture 8: Train the model

Lecture 9: Use the model for predictions

Chapter 2: Using the model in production

Lecture 1: Create the Python module

Chapter 3: Setting up your development environment

Lecture 1: Setting up your local development environment

Lecture 2: Setting up deep learning environment on AWS

Instructors

Dovydas Ceilutka
Machine Learning Engineer

Rating Distribution

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

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