This course is used in various fields such as automobiles, aerospace, electronics, and medicine deep learningI'm dealing with it.
deep learningis a method of artificial intelligence (AI) technology that teaches computers to process data in a way inspired by the human brain.
It can recognize complex patterns in pictures, text, sound, and other data to generate accurate insights and predictions. It's something that generally requires human intelligence to automate tasks.
deep learningThese are the amazing things they do.
- It automatically detects paint signs and pedestrians in autonomous vehicles.
- The defense system automatically flags regions of interest in satellite images.
- Cancer cells are automatically detected by analyzing medical images during the diagnosis process.
- It automatically detects when a person or object is within an unsafe distance.
Even using transition models based on TensorFlow 2.0!
✅ This lesson is difficult deep learningThis is the class that solved it in the easiest and clearest way.
Using practical topics such as election voter prediction, patient prediction, and images, we will cover the entire deep learning process by communicating difficult concepts such as data scaling, learning unit settings, learning rate/hidden layer/number of neurons, weight initialization, activation function selection, application of high-speed optimizers, and overfit regulation in the easiest way.
- Master the core concepts of deep learning and the theory of deep learning algorithms and core models such as DNN, CNN, and RNN
- Through scaling of collected data and segmentation of train/test data, etc., it is possible to directly predict quantitative data, images, documents, etc., and experience practical data analysis
- Derive the optimal model with the highest predictive power by learning various hyperparameter tuning methods from the built deep learning model
- Business practitioners and job-seekers who want to become AI data analysts
- A developer who wants to improve predictability and automate processes through deep learning
- Those who want to improve the efficiency and predictability of repetitive tasks by learning deep learning algorithms
- Researchers who want to produce research results using the latest deep learning techniques in addition to traditional statistical analysis
There are 2 reasons why this class is special
① Deep learning lectures taught by data analysis experts with over 20 years of experience
② Practical preparation curriculum that performs the entire analysis process with various practical topics
We have conducted training for professors, researchers, practitioners, universities (institutes), and job-seekers through over 20 years of expertise in statistical analysis and big data analysis. Data analysis is no longer an option; it's a necessity. Starting with Python, a big data analyst certificate, and a social research analyst certificate, we can solve everything at once at Data Campus. The highly specialized curriculum strengthens the capacity of data analysts and fosters practical skills.