This is a practical course on deep learning using DNN, CNN, and RNN

DNN, CNN, RNN?

A deep learning practice course that completely organizes the core algorithms of deep learning through this course, even technical terms that seem difficult and actually uses them

I learn something like this!

Understanding the deep learning development process
Understand the components and modeling principles of DNN, CNN, and RNN
Understanding the various frameworks in Tensorflow Keras
Ability to use deep learning algorithms through various deep learning exercises

Deep learning core algorithms DNN, CNN, RNN!

Understand it through various exercises and actually use it!

I want to try deep learning in earnest!

The era of the Fourth Industrial RevolutionIn AI technologyThis is becoming more important than anything else.

Therefore, many companies are also actively hiring AI experts, and there is a forecast that many jobs will disappear in the future.

Of course, AI has yet to stand out in art and creation, which were thought to be unique to humans, but it will only be a matter of time before it is gradually replaced.

Deep learning technology is a technology that anyone working in the IT industry would like to try, but the reality is that the entry barrier is so high that it's not easy to take on the challenge.

Therefore, I saw it at Maso Campus so that you can build up knowledge related to deep learning Designed so that anyone can follow the deep learning courseI did it.

To do this, you need to learn and learn about new deep learning algorithms.

This <Deep learning practice using DNN, CNN, and RNN> course Python (Python) language and Tensorflow Keras (Tensorflow Keras) frameworkThis is a deep learning algorithm model development process based on

In the future, it will be important to secure technology to extract useful information from more data.

Artificial intelligence (AI) -based machine learning/deep learning technologies have emerged to solve these problems, and the main models used to implement them are DNN with supervised learning, CNN with unsupervised learning, and RNN with reinforcement learningI have it.

Take a look at the overall development process of deep learning, cover in detail the learning process of developing deep learning models with various algorithms, find out the pros, cons, and application case exercises for each model, check the differences between each model by entering actual code, and use deep learning algorithms!

I recommend it to people like this

Practitioners who want to try using artificial intelligence in their work
Anyone who wants to build a career in the IT industry, such as starting a business/transfer/joining a company
Executives and practitioners who want to introduce artificial intelligence into their business
Anyone who wants to get started right from the first button to build deep learning capabilities

After listening to deep learning practices using DNN, CNN, and RNN

<Deep learning practices using DNN, CNN, and RNN> LecturesAfter listening to it,

You can secure the following competencies.

Deep learning development processUnderstanding of
DNN, CNN, RNN's The principles of components and models uptake
Tensorflow Keras's Various frameworksUnderstanding
Through various deep learning exercises Ability to use deep learning

Regardless of the field Overwhelming increase in productivityDeep learning brings!

Through a detailed explanation of the core algorithms of deep learning Learn in-depth theory and practice at the same timeThe process of doing it!

Course features

Through this course, it is currently the hottest deep learning algorithm How DNN, CNN, and RNN workThrough understanding and practice Implement deep learning models in practiceYou can do it.

Step 1. Understanding the concepts and operating processes of DNN, CNN, and RNN

What are DNN, CNN, and RNN among the many deep learning algorithms,

Because it shows a different level of performance depending on what kind of algorithm is used in what situation Let's take a closer look at each principle I'll dig it up!

Step 2. Practice a deep learning modeling course

Typical deep learning algorithms, regression and classification!

DNN, CNN, and RNN can perform regression and classification much more sophisticated and accurate than machine learning!

Various exercises with a deep learning algorithm model I designed myselfThrough Use it right awayYou can try deep learning that you can do.

Step 3. Bringing insights from the digital world to the real world!

If insights obtained after designing and training models using various techniques of deep learning algorithms are applied to actual work,

Extensive aspects of sales, development, and human resources data-driven A revolutionary advance in decision makingYou can import

Learning content

1. Design a multiple linear regression model!

2. Visualize MNIST handwriting model evaluation results!

3. CNN components!

4. Run the model with CNN!

5. Classifying news categories using LSTM!

Expected Questions Q&A

Q. Do I need player knowledge of Python programming?

A. Basic Python skills are required for this course and subsequent deep learning courses at Maso Campus. If you are unfamiliar with Python, we recommend that you first take the “Introduction to Python Data Analysis” and “Python Data Analysis Practice” courses at Maso Campus.

Q. Are there any requirements or requirements to take the course?

A. Since this is a practice-oriented course, it is a good idea to prepare a dual monitor or an extra device that can separate the lecture screen from the practice screen. Also, since exercises are conducted based on Windows OS, we recommend taking courses in a Windows environment.

Q. I heard that deep learning requires a high-spec PC, but do I need a high-spec PC for practice?

A. Although it is recommended to run it in a high-spec environment, in this course, exercises are conducted in a virtual environment using Anaconda and Jupyter notebooks, so there is no difficulty in taking the course if it is at the level of a typical business PC.