A Complete Guide to Deep Learning CNN - TensorFlow Keras Version
dooleyz3525
₩85
내일까지
29%
₩59
초급 / Deep Learning(DL), CNN, Tensorflow, Keras, Kaggle, Machine Learning(ML)
4.9
(119)
From core theories of Deep Learning and CNN to implementation methods of various CNN models, and practical Deep Learning development know-how through real-world problems, If you want to become a Deep Learning CNN technology expert, join us in this lecture :)
초급
Deep Learning(DL), CNN, Tensorflow
A Complete Guide to Deep Learning CNN - TensorFlow Keras Version
dooleyz3525
₩85
내일까지
29%
₩59
초급 / Deep Learning(DL), CNN, Tensorflow, Keras, Kaggle, Machine Learning(ML)
4.9
(119)
![[Revised Edition] Deep Learning Computer Vision: The Complete Guide강의 썸네일](https://cdn.inflearn.com/public/courses/325035/cover/f4bbef4d-d9a9-4def-a3a5-738a9eed8245/325035-eng.jpg?f=avif&w=420)
[Revised Edition] Deep Learning Computer Vision: The Complete Guide
dooleyz3525
₩94
내일까지
29%
₩66
중급이상 / Python, Machine Learning(ML), Deep Learning(DL), Computer Vision(CV)
4.9
(165)
This course will help you grow into a deep learning-based computer vision expert needed in the field through in-depth theoretical explanations of Object Detection and Segmentation, along with practical examples at a level that can be immediately applied in the industry.
중급이상
Python, Machine Learning(ML), Deep Learning(DL)
[Revised Edition] Deep Learning Computer Vision: The Complete Guide
dooleyz3525
₩94
내일까지
29%
₩66
중급이상 / Python, Machine Learning(ML), Deep Learning(DL), Computer Vision(CV)
4.9
(165)
Introduction to Machine Learning/Deep Learning and Python Introductory Course for Learning
YoungJea Oh
₩9
입문 / Machine Learning(ML), Deep Learning(DL), Python, Numpy, Pandas, Matplotlib
4.8
(40)
You can acquire an overview of machine learning and deep learning, how to use basic tools, and the Python language knowledge necessary for learning in a short period of time.
입문
Machine Learning(ML), Deep Learning(DL), Python
Introduction to Machine Learning/Deep Learning and Python Introductory Course for Learning
YoungJea Oh
₩9
입문 / Machine Learning(ML), Deep Learning(DL), Python, Numpy, Pandas, Matplotlib
4.8
(40)
MLflow with Silicon Valley Engineers
altoformula
₩43
7일만
23%
₩33
입문 / mlflow, Machine Learning(ML), mlops, Deep Learning(DL), AI
4.7
(20)
Are you still managing ML experiments manually? 🤔 Automate everything from experiment tracking to model deployment with MLflow, and dramatically boost your development productivity! An essential skill for data scientists and ML engineers 💡 Start right now! 🚀
입문
mlflow, Machine Learning(ML), mlops
MLflow with Silicon Valley Engineers
altoformula
₩43
7일만
23%
₩33
입문 / mlflow, Machine Learning(ML), mlops, Deep Learning(DL), AI
4.7
(20)
Introduction to Deep Learning Natural Language Processing with Examples NLP with TensorFlow - From RNN to BERT
AISchool
₩68
초급 / Deep Learning(DL), NLP, Tensorflow
4.5
(33)
From the basics of deep learning natural language processing to the latest models such as Transformer and BERT, learn the principles and utilization methods of deep learning natural language processing (NLP) through various examples and practical code implementations.
초급
Deep Learning(DL), NLP, Tensorflow
Introduction to Deep Learning Natural Language Processing with Examples NLP with TensorFlow - From RNN to BERT
AISchool
₩68
초급 / Deep Learning(DL), NLP, Tensorflow
4.5
(33)
Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma
AISchool
₩43
중급이상 / openAI API, ChatGPT, gemini, Gemma, multimodal, LLM, Deep Learning(DL), streamlit
4.8
(10)
This course will teach you the concept of the Google Gemini model and how to use the Gemini API, and create various AI applications using Streamlit.
중급이상
openAI API, ChatGPT, gemini
Large-Scale Language Models for Everyone LLM Part 3 - Building AI Applications with Google Gemini API, OpenAI API, and Gemma
AISchool
₩43
중급이상 / openAI API, ChatGPT, gemini, Gemma, multimodal, LLM, Deep Learning(DL), streamlit
4.8
(10)
Data Science(DS) and AI Learning & Career Guide for Non-Majors/Beginners
AISchool
₩23
28%
₩17
입문 / Deep Learning(DL), Machine Learning(ML)
5.0
(40)
Data Science(DS) & Artificial Intelligence(AI) job role analysis, plus a learning & employment roadmap for building a career in these roles.
입문
Deep Learning(DL), Machine Learning(ML)
Data Science(DS) and AI Learning & Career Guide for Non-Majors/Beginners
AISchool
₩23
28%
₩17
입문 / Deep Learning(DL), Machine Learning(ML)
5.0
(40)
TensorFlow Object Detection API Guide Part 1 - Detecting Objects with 10 Lines of Code
AISchool
₩26
초급 / Tensorflow, Deep Learning(DL), CNN
4.8
(33)
This course teaches you how to perform Object Detection using the latest high-performance deep learning model using the TensorFlow Object Detection API through simple Colab exercises, and learns the principles of the latest deep learning Object Detection models.
초급
Tensorflow, Deep Learning(DL), CNN
TensorFlow Object Detection API Guide Part 1 - Detecting Objects with 10 Lines of Code
AISchool
₩26
초급 / Tensorflow, Deep Learning(DL), CNN
4.8
(33)
Linear Algebra Leading to Machine Learning/Deep Learning
dlbro
₩43
입문 / Linear Algebra, Machine Learning(ML), Deep Learning(DL)
4.5
(45)
Covers essential linear algebra for Machine Learning/Deep Learning research.
입문
Linear Algebra, Machine Learning(ML), Deep Learning(DL)
Linear Algebra Leading to Machine Learning/Deep Learning
dlbro
₩43
입문 / Linear Algebra, Machine Learning(ML), Deep Learning(DL)
4.5
(45)
Understanding the concept of deep learning leading to practical artificial intelligence
dlbro
₩55
입문 / Deep Learning(DL), Artificial Neural Network, Machine Learning(ML)
4.7
(107)
This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.
입문
Deep Learning(DL), Artificial Neural Network, Machine Learning(ML)
Understanding the concept of deep learning leading to practical artificial intelligence
dlbro
₩55
입문 / Deep Learning(DL), Artificial Neural Network, Machine Learning(ML)
4.7
(107)
AI-based recommendation system
YoungJea Oh
₩39
중급이상 / Deep Learning(DL), Machine Learning(ML), Recommendation System, Python, Tensorflow
4.4
(8)
This course covers everything from the basic concepts of recommendation systems to the principles of applying deep learning. Learn about various recommendation algorithms such as collaborative filtering, content-based filtering, and hybrid recommendation systems, and develop practical skills for developing recommendation services!
중급이상
Deep Learning(DL), Machine Learning(ML), Recommendation System
AI-based recommendation system
YoungJea Oh
₩39
중급이상 / Deep Learning(DL), Machine Learning(ML), Recommendation System, Python, Tensorflow
4.4
(8)
From Introduction to Reinforcement Learning to Deep Q-learning/Policy Gradient
YoungJea Oh
₩43
중급이상 / Deep Learning(DL), Reinforcement Learning(RL), Python, PyTorch
4.7
(34)
All the recent amazing achievements in the field of artificial intelligence have been announced in the field of reinforcement learning. We have covered reinforcement learning technology, which is revolutionizing true artificial intelligence technology such as robots, autonomous driving technology, and human-like machines, from the basics to the advanced level, in an easy-to-understand way for beginners.
중급이상
Deep Learning(DL), Reinforcement Learning(RL), Python
From Introduction to Reinforcement Learning to Deep Q-learning/Policy Gradient
YoungJea Oh
₩43
중급이상 / Deep Learning(DL), Reinforcement Learning(RL), Python, PyTorch
4.7
(34)
The First Step into AI Without Math: From Basics to the Latest Trends
jihoonkim
₩59
입문 / Machine Learning(ML), Deep Learning(DL)
4.8
(129)
This lecture is designed to give you a general understanding of AI without overwhelming you with difficult topics like mathematical formulas. It's perfect for learning with a light and easy mindset.
입문
Machine Learning(ML), Deep Learning(DL)
The First Step into AI Without Math: From Basics to the Latest Trends
jihoonkim
₩59
입문 / Machine Learning(ML), Deep Learning(DL)
4.8
(129)
Deep Learning Paper Implementation with YOLO Implementation with TensorFlow 2.0
AISchool
₩77
중급이상 / Deep Learning(DL), Tensorflow
4.7
(38)
This course teaches you how to implement deep learning papers by implementing the YOLO (You Only Look Once) paper from scratch using TensorFlow 2.0.
중급이상
Deep Learning(DL), Tensorflow
Deep Learning Paper Implementation with YOLO Implementation with TensorFlow 2.0
AISchool
₩77
중급이상 / Deep Learning(DL), Tensorflow
4.7
(38)
Practical Docker: Creating your own deep learning cloud computer with Docker
danielyouk
₩59
초급 / Docker, Virtualization, Python, Deep Learning(DL), mlops, Azure, Linux, azure-data-lake-gen2
4.7
(15)
You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.
초급
Docker, Virtualization, Python
Practical Docker: Creating your own deep learning cloud computer with Docker
danielyouk
₩59
초급 / Docker, Virtualization, Python, Deep Learning(DL), mlops, Azure, Linux, azure-data-lake-gen2
4.7
(15)
Machine Learning with JavaScript and Tensorflow.js
YoungJea Oh
₩43
초급 / Machine Learning(ML), Deep Learning(DL), JavaScript, tensorflow-js
5.0
(3)
JavaScript, which is known to all web developers, now explore the world of machine learning with this powerful language! This course learns how to build and deploy machine learning models using JavaScript and the powerful machine learning library Tensorflow.js. It guides you step-by-step through all the technologies required to develop web-based machine learning applications. Through this course, learners will systematically understand the core principles of machine learning. In addition, you will learn how to develop deep learning models using JavaScript and Tensorflow.js APIs, how to utilize transfer learning based on pre-trained models, and how to apply all this knowledge interactively in a browser environment.
초급
Machine Learning(ML), Deep Learning(DL), JavaScript
Machine Learning with JavaScript and Tensorflow.js
YoungJea Oh
₩43
초급 / Machine Learning(ML), Deep Learning(DL), JavaScript, tensorflow-js
5.0
(3)
Techniques for detecting abnormal transactions using artificial intelligence
YoungJea Oh
₩43
중급이상 / Machine Learning(ML), Deep Learning(DL)
4.6
(24)
In the modern business world, data security and fraud prevention have become more important than ever. This lecture focuses on how to effectively detect and analyze fraudulent transactions using artificial intelligence (AI). Using Python and machine learning, we will build an AI model that can detect and detect anomalies in various industries, such as fraudulent transactions, credit card fraud, and production line abnormalities, early.
중급이상
Machine Learning(ML), Deep Learning(DL)
Techniques for detecting abnormal transactions using artificial intelligence
YoungJea Oh
₩43
중급이상 / Machine Learning(ML), Deep Learning(DL)
4.6
(24)
Natural Language Processing (NLP) with Deep Learning (From Basics to ChatGPT/Generative Models)
YoungJea Oh
₩68
중급이상 / Deep Learning(DL), NLP, Tensorflow
4.9
(27)
Natural Language Processing (NLP) is one of the fastest growing areas of artificial intelligence. This course covers a wide range of topics, from the basics of NLP to the latest NLP techniques using deep learning. In particular, it provides an in-depth understanding of cutting-edge generative models such as ChatGPT.
중급이상
Deep Learning(DL), NLP, Tensorflow
Natural Language Processing (NLP) with Deep Learning (From Basics to ChatGPT/Generative Models)
YoungJea Oh
₩68
중급이상 / Deep Learning(DL), NLP, Tensorflow
4.9
(27)
Introduction to Machine Learning and Deep Learning Using Python
YoungJea Oh
₩52
입문 / Machine Learning(ML), Deep Learning(DL), Python, Numpy, Pandas, Matplotlib, Anaconda, Tensorflow, Keras, CNN
4.9
(66)
Do you want to take your first step into the world of data? Learn machine learning and deep learning, the core technologies of AI, with Python. This course will guide you step by step, from the basics of machine learning and deep learning to practical applications. Traditional machine learning and deep learning are based on many of the same principles and technical systems. Therefore, this course does not separate the two into separate subjects, but rather organizes them into one connected course so that beginners can increase their understanding of machine learning as a whole.
입문
Machine Learning(ML), Deep Learning(DL), Python
Introduction to Machine Learning and Deep Learning Using Python
YoungJea Oh
₩52
입문 / Machine Learning(ML), Deep Learning(DL), Python, Numpy, Pandas, Matplotlib, Anaconda, Tensorflow, Keras, CNN
4.9
(66)
A Machine Learning Story Explained in Simple Terms That Even a Die-Hard Liberal Arts Student Can Understand at Once
sdlee
무료
입문 / Machine Learning(ML), Deep Learning(DL)
4.7
(50)
This is a machine learning lecture written in easy-to-understand language, like a story, without any formulas—tailored perfectly for those who are humanities students to the core!
입문
Machine Learning(ML), Deep Learning(DL)
A Machine Learning Story Explained in Simple Terms That Even a Die-Hard Liberal Arts Student Can Understand at Once
sdlee
무료
입문 / Machine Learning(ML), Deep Learning(DL)
4.7
(50)
![[AI Practice] Getting Started with Paper Implementation for AI Research Engineers with PyTorch강의 썸네일](https://cdn.inflearn.com/public/courses/334289/cover/b8885796-1e67-4983-9432-bcda0daae927/334289.png?f=avif&w=420)
[AI Practice] Getting Started with Paper Implementation for AI Research Engineers with PyTorch
whitebox
₩43
중급이상 / Deep Learning(DL), AI, PyTorch, Computer Vision(CV), Python
5.0
(35)
When researching AI or conducting a project using it, basic paper implementation is essential. Let's upgrade our practical skills by implementing an actual paper through this lecture!
중급이상
Deep Learning(DL), AI, PyTorch
[AI Practice] Getting Started with Paper Implementation for AI Research Engineers with PyTorch
whitebox
₩43
중급이상 / Deep Learning(DL), AI, PyTorch, Computer Vision(CV), Python
5.0
(35)
Deep Learning Next Generation Innovation Technology - Introduction to Physical Information Neural Networks and Pytorch Practice
dlbro
₩55
초급 / PyTorch, Deep Learning(DL), Machine Learning(ML), Artificial Neural Network
4.8
(22)
This is a lecture that studies the physical information neural network, one of the next-generation innovative technologies of deep learning, and implements it directly using Pytorch. Let's learn the next-generation innovative technology of artificial intelligence with me!
초급
PyTorch, Deep Learning(DL), Machine Learning(ML)
Deep Learning Next Generation Innovation Technology - Introduction to Physical Information Neural Networks and Pytorch Practice
dlbro
₩55
초급 / PyTorch, Deep Learning(DL), Machine Learning(ML), Artificial Neural Network
4.8
(22)
Deep Learning Framework Made with Excel
hjk1000
₩18
초급 / VBA, Deep Learning(DL), Excel, gan, Reinforcement Learning(RL)
Let's implement a deep learning framework directly with Excel! Let's solve supervised learning/unsupervised learning/reinforcement learning with the implemented framework!
초급
VBA, Deep Learning(DL), Excel
Deep Learning Framework Made with Excel
hjk1000
₩18
초급 / VBA, Deep Learning(DL), Excel, gan, Reinforcement Learning(RL)
Complete mastery of deep learning theory + PyTorch practice
peterbyun969574
₩220
초급 / Deep Learning(DL), PyTorch, Computer Vision(CV), NLP, transformer, CNN, RNN, LLM
4.9
(66)
This course teaches the “core concepts” of deep learning required to work in the deep learning field and the practical skills required to perform actual deep learning projects through hands-on training using PyTorch.
초급
Deep Learning(DL), PyTorch, Computer Vision(CV)
Complete mastery of deep learning theory + PyTorch practice
peterbyun969574
₩220
초급 / Deep Learning(DL), PyTorch, Computer Vision(CV), NLP, transformer, CNN, RNN, LLM
4.9
(66)
Artificial Intelligence Basics and Career Advice for Non-Majors/High School Students
coco
₩34
29%
₩24
입문 / Machine Learning(ML), Deep Learning(DL)
5.0
(1)
This is a lecture for non-majors or high school students who are studying data science and artificial intelligence for the first time. We will teach you the concepts of artificial intelligence and machine learning and what efforts you need to make to get a related job.
입문
Machine Learning(ML), Deep Learning(DL)
Artificial Intelligence Basics and Career Advice for Non-Majors/High School Students
coco
₩34
29%
₩24
입문 / Machine Learning(ML), Deep Learning(DL)
5.0
(1)
License Plate Recognition Project and Deep Learning Image Recognition All-in-One with TensorFlow
AISchool
₩110
초급 / Tensorflow, Deep Learning(DL), Machine Learning(ML), CNN, NLP, Computer Vision(CV)
4.8
(73)
This is an all-in-one course where you can learn the entire process from the basics of deep learning, TensorFlow, and computer vision to practical applications through a real-world license plate recognition project. Through various hands-on exercises, you can develop the practical skills to apply the latest deep learning models to custom datasets.
초급
Tensorflow, Deep Learning(DL), Machine Learning(ML)
License Plate Recognition Project and Deep Learning Image Recognition All-in-One with TensorFlow
AISchool
₩110
초급 / Tensorflow, Deep Learning(DL), Machine Learning(ML), CNN, NLP, Computer Vision(CV)
4.8
(73)
Computer Vision All-in-One: 10 Practical Projects Completed in 12 Hours
nomad
₩153
초급 / Python, OpenCV, Deep Learning(DL), Machine Learning(ML), yolo, image-segmentation
3.2
(5)
Easy, Usable Computer Vision Projects: Step-by-step learning of practical CV projects. Boost skill with real examples.
초급
Python, OpenCV, Deep Learning(DL)
Computer Vision All-in-One: 10 Practical Projects Completed in 12 Hours
nomad
₩153
초급 / Python, OpenCV, Deep Learning(DL), Machine Learning(ML), yolo, image-segmentation
3.2
(5)
Time series data processing using Python and deep learning
YoungJea Oh
₩39
중급이상 / AI, python3, Deep Learning(DL), Financial Engineering, Algorithm, Investment
4.8
(17)
Time is constantly flowing, and data is constantly accumulating. In this dynamic world, time series data plays a vital role in every aspect of our lives. From the volatility of financial markets to subtle signals of climate change, time series data captures it all. Now learn how to interpret and leverage this powerful data using the power of Python and deep learning!
중급이상
AI, python3, Deep Learning(DL)
Time series data processing using Python and deep learning
YoungJea Oh
₩39
중급이상 / AI, python3, Deep Learning(DL), Financial Engineering, Algorithm, Investment
4.8
(17)
Deep Learning and TensorFlow for Beginners: The Basics Fast
Jay
₩9
초급 / Deep Learning(DL), Tensorflow, Python, colab
4.9
(47)
This is a lecture where you can learn Deep Learning using TensorFlow. Learn linear regression, logistic regression, and softmax regression models, and finally create an MLP model that can classify fashion images!
초급
Deep Learning(DL), Tensorflow, Python
Deep Learning and TensorFlow for Beginners: The Basics Fast
Jay
₩9
초급 / Deep Learning(DL), Tensorflow, Python, colab
4.9
(47)
![[Pytorch] Building Deep Learning Models with Pytorch강의 썸네일](https://cdn.inflearn.com/public/courses/329226/cover/056ed444-5b26-40fc-b4d6-8e03b2f23890/DL_pytorch.jpg?f=avif&w=420)
[Pytorch] Building Deep Learning Models with Pytorch
YoungJea Oh
₩43
초급 / PyTorch, Anaconda, CNN, Deep Learning(DL), Artificial Neural Network
5.0
(11)
Learn how to build deep learning models directly through intuitive and Pythonic PyTorch. This reflects the latest PyTorch version.
초급
PyTorch, Anaconda, CNN
[Pytorch] Building Deep Learning Models with Pytorch
YoungJea Oh
₩43
초급 / PyTorch, Anaconda, CNN, Deep Learning(DL), Artificial Neural Network
5.0
(11)
How does artificial intelligence learn? - Learning AI principles for fun
AI CASTLE
₩17
입문 / Machine Learning(ML), Deep Learning(DL), Reinforcement Learning(RL)
4.7
(57)
A general education lecture for the public to shed the vague fear of artificial intelligence. Through concrete examples, we learn what AI learning truly means. Also, via specific examples, we examine AI's 'brain structure' and how it thinks.
입문
Machine Learning(ML), Deep Learning(DL), Reinforcement Learning(RL)
How does artificial intelligence learn? - Learning AI principles for fun
AI CASTLE
₩17
입문 / Machine Learning(ML), Deep Learning(DL), Reinforcement Learning(RL)
4.7
(57)
Deep Learning with Keras
jikim1770
₩68
초급 / Deep Learning(DL), Keras, CNN, RNN
Understand the principles of deep learning and use Keras to simplify the complexity of building and training neural networks using models, layers, and optimization techniques.
초급
Deep Learning(DL), Keras, CNN
Deep Learning with Keras
jikim1770
₩68
초급 / Deep Learning(DL), Keras, CNN, RNN
Triangles in action! OpenAI Triton beginner
triangle
₩116
초급 / Deep Learning(DL), Python, gpgpu, triton, openai, kernel-programming, CNN, dropout, relu, argmax
4.1
(7)
In this course, you will learn how to program kernels and develop PyTorch modules. You can use the knowledge you have gained to develop models faster.
초급
Deep Learning(DL), Python, gpgpu
Triangles in action! OpenAI Triton beginner
triangle
₩116
초급 / Deep Learning(DL), Python, gpgpu, triton, openai, kernel-programming, CNN, dropout, relu, argmax
4.1
(7)
Deep Learning with Excel
hjk1000
₩4
입문 / Excel, Deep Learning(DL), VBA
4.8
(20)
Let's learn the principles of deep learning by visualizing them with Excel.
입문
Excel, Deep Learning(DL), VBA
Deep Learning with Excel
hjk1000
₩4
입문 / Excel, Deep Learning(DL), VBA
4.8
(20)
Large Language Model for Everyone LLM (Large Language Model) Part 1 - Try Fine-Tuning Llama 2
AISchool
₩68
중급이상 / LLM, Llama, Deep Learning(DL), PyTorch, ChatGPT
4.6
(99)
We will learn step by step from the basic concepts of LLM (Large Language Model) to how to fine-tune the Llama 2 model, a high-performance LLM, on the dataset of your choice.
중급이상
LLM, Llama, Deep Learning(DL)
Large Language Model for Everyone LLM (Large Language Model) Part 1 - Try Fine-Tuning Llama 2
AISchool
₩68
중급이상 / LLM, Llama, Deep Learning(DL), PyTorch, ChatGPT
4.6
(99)
Learning Deep Learning Paper Implementation through GPT Paper Implementation with TensorFlow 2.0 Part 1
AISchool
₩85
중급이상 / gpt, Tensorflow, Deep Learning(DL)
1.0
(1)
A course to learn deep learning paper implementation skills, implementing the GPT-1 (Improving Language Understanding by Generative Pre-Training) paper from scratch with TensorFlow 2.0.
중급이상
gpt, Tensorflow, Deep Learning(DL)
Learning Deep Learning Paper Implementation through GPT Paper Implementation with TensorFlow 2.0 Part 1
AISchool
₩85
중급이상 / gpt, Tensorflow, Deep Learning(DL)
1.0
(1)
Deep Learning Paper Implementation with U-Net Implementation with TensorFlow 2.0 - Deep Learning Medical Image Analysis
AISchool
₩77
중급이상 / Tensorflow, Deep Learning(DL)
4.5
(8)
This course teaches you how to implement deep learning papers by implementing the U-Net paper from scratch using TensorFlow 2.0.
중급이상
Tensorflow, Deep Learning(DL)
Deep Learning Paper Implementation with U-Net Implementation with TensorFlow 2.0 - Deep Learning Medical Image Analysis
AISchool
₩77
중급이상 / Tensorflow, Deep Learning(DL)
4.5
(8)
(UPDATED) Personalized Recommendation Systems using Python | Recommendation Algorithms | Recommendation AI
거친코딩
₩34
초급 / Recommendation System, Deep Learning(DL)
4.7
(42)
Create your own personalized recommendation algorithm by understanding how various recommendation algorithm principles work!
초급
Recommendation System, Deep Learning(DL)
(UPDATED) Personalized Recommendation Systems using Python | Recommendation Algorithms | Recommendation AI
거친코딩
₩34
초급 / Recommendation System, Deep Learning(DL)
4.7
(42)
From the concept of the latest deep learning technology Vision Transformer to Pytorch implementation
dlbro
₩66
중급이상 / Vision Transformer, Deep Learning(DL), PyTorch, Computer Vision(CV)
4.8
(97)
This is a lecture that studies Vision Transformer, one of the latest deep learning technologies, and implements a paper using Pytorch. Come experience the new future of the vision field with me!
중급이상
Vision Transformer, Deep Learning(DL), PyTorch
From the concept of the latest deep learning technology Vision Transformer to Pytorch implementation
dlbro
₩66
중급이상 / Vision Transformer, Deep Learning(DL), PyTorch, Computer Vision(CV)
4.8
(97)
Kim Il-han's Practical Application of TensorFlow2 + Keras Library for Artificial Intelligence
softcampus
₩18
초급 / Tensorflow, Keras, Deep Learning(DL)
5.0
(3)
In this course, you will learn how to use the Tensorflow library to make data predictions. You will learn data analysis and processing methods that can be applied in practice by learning the library and analyzing sample data in parallel.
초급
Tensorflow, Keras, Deep Learning(DL)
Kim Il-han's Practical Application of TensorFlow2 + Keras Library for Artificial Intelligence
softcampus
₩18
초급 / Tensorflow, Keras, Deep Learning(DL)
5.0
(3)
