Business card recognition function implementation course using OpenCV

Basic / 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.

Basic

Tensorflow, Deep Learning(DL), CNN

TensorFlow Object Detection API Guide Part 1 - Detecting Objects with 10 Lines of Code

AISchool

Basic / Tensorflow, Deep Learning(DL), CNN

4.8

(33)

First-Time Deep Learning and PyTorch Bootcamp (Easy! From the Basics to the Core Transformers Behind ChatGPT) [Data Analysis/Science Part 3]

funcoding

$68.20

Basic / Deep Learning(DL), PyTorch, Machine Learning(ML), Artificial Neural Network, Vision Transformer

4.9

(99)

1,700+

This course has been newly designed to help you gradually learn the mathematics and theory needed to understand deep learning, PyTorch-based implementation, transfer learning, and the core GPT Transformer, based on the instructor’s experience of struggling when first learning deep learning.

Basic

Deep Learning(DL), PyTorch, Machine Learning(ML)

First-Time Deep Learning and PyTorch Bootcamp (Easy! From the Basics to the Core Transformers Behind ChatGPT) [Data Analysis/Science Part 3]

funcoding

$68.20

Basic / Deep Learning(DL), PyTorch, Machine Learning(ML), Artificial Neural Network, Vision Transformer

4.9

(99)

1,700+

OpenCV + WebApp (Making a Face Eye Detection Web App)

Jeonghyun Kim

Basic / Django, Web Application, OpenCV, Computer Vision(CV)

4.3

(12)

Let's create a web app that uploads an image and uses OpenCV to process it and detect faces.

Basic

Django, Web Application, OpenCV

OpenCV + WebApp (Making a Face Eye Detection Web App)

Jeonghyun Kim

Basic / Django, Web Application, OpenCV, Computer Vision(CV)

4.3

(12)

[AI Practice] Getting Started with Paper Implementation for AI Research Engineers with PyTorch

whitebox

Intermediate / Deep Learning(DL), AI, PyTorch, Computer Vision(CV), Python

5.0

(36)

400+

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!

Intermediate

Deep Learning(DL), AI, PyTorch

[AI Practice] Getting Started with Paper Implementation for AI Research Engineers with PyTorch

whitebox

Intermediate / Deep Learning(DL), AI, PyTorch, Computer Vision(CV), Python

5.0

(36)

400+

Creating an AI Portfolio - Airbnb Clone Project

AISchool

Basic / Deep Learning(DL), Portfolio, GitHub

4.6

(9)

This course allows you to build an AI portfolio by cloning the Amenity Detection project from the Airbnb Data Science team—a prime example of TensorFlow utilization—and documenting the entire process on a GitHub blog.

Basic

Deep Learning(DL), Portfolio, GitHub

Creating an AI Portfolio - Airbnb Clone Project

AISchool

Basic / Deep Learning(DL), Portfolio, GitHub

4.6

(9)

[AI Practice] Understanding Diffusion Models through Prompt-to-prompt Paper Implementation

dongdong1

$30.80

Intermediate / Python, Deep Learning(DL), PyTorch, AI

4.8

(9)

This course conducts hands-on practice related to Diffusion models among generative artificial intelligence models. By reading and implementing the prompt-to-prompt paper, which is a representative Diffusion model application paper, we expect to cultivate the ability to understand the latest artificial intelligence papers.

Intermediate

Python, Deep Learning(DL), PyTorch

[AI Practice] Understanding Diffusion Models through Prompt-to-prompt Paper Implementation

dongdong1

$30.80

Intermediate / Python, Deep Learning(DL), PyTorch, AI

4.8

(9)

[Mobile] Deep Learning Computer Vision Practical Project

nomad

Intermediate / IONIC, Machine Learning(ML), Deep Learning(DL), OpenCV, Computer Vision(CV)

4.3

(4)

AI Artificial Intelligence, it goes without saying that mobile is the trend. But how do you learn machine learning and deep learning and use them on mobile? Now, let's learn useful mobile Computer Vision projects that are used in daily life.

Intermediate

IONIC, Machine Learning(ML), Deep Learning(DL)

[Mobile] Deep Learning Computer Vision Practical Project

nomad

Intermediate / IONIC, Machine Learning(ML), Deep Learning(DL), OpenCV, Computer Vision(CV)

4.3

(4)

Building an MNIST NPU with FPGA — From RTL to Bit-True Verification

EdgeChipLab

$203.50

Intermediate / Artificial Neural Network, Computer Vision(CV), Verilog HDL, FPGA, verification, AI, rtl

Putting a neural network on an FPGA—the phrase is familiar, but few have actually done it. If you want to stay a step ahead in capstone projects, competitions, or graduation projects, you must be able to go beyond just training a model and actually build and prove how those computations run inside a real chip. This course bridges that exact gap between theory and physical hardware. You will complete a neural network accelerator (NPU) for MNIST digit recognition from start to finish—from reading specifications to Python golden models, Verilog RTL design, and FPGA verification. From Conv layers made with line buffers and parallel MACs, through ReLU, MaxPool, and Flatten, to fully connected layers and Argmax—you will integrate nine blocks into a single chip and prove for yourself that "the Python reference and the hardware output do not differ by even a single bit (Bit-True)." I have even included how to overcome those frustrating moments when the simulation runs fine but the results are subtly different. I will guide you through practical know-how that general deep learning textbooks don't cover, such as integer quantization, array axis reordering, and accumulator overflow prevention. I have distilled the trial and error I experienced over years of RISC-V CPU design and FPGA Bit-True verification into this course so that you don't have to repeat them. By the end of the class, you will have a completed hardware project that allows you to say, "I designed and verified it myself."

Intermediate

Artificial Neural Network, Computer Vision(CV), Verilog HDL

Building an MNIST NPU with FPGA — From RTL to Bit-True Verification

EdgeChipLab

$203.50

Intermediate / Artificial Neural Network, Computer Vision(CV), Verilog HDL, FPGA, verification, AI, rtl

Building OCR that actually works in real-world scenarios, here's how to do it.

nexthumans

$84.70

Basic / Python, AI, openai, openAI API, Computer Vision(CV)

4.7

(6)

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

Basic

Python, AI, openai

Building OCR that actually works in real-world scenarios, here's how to do it.

nexthumans

$84.70

Basic / Python, AI, openai, openAI API, Computer Vision(CV)

4.7

(6)

[7-Day Complete] Pass MS AI-900 Certification in One Go

jobgreegi

$34.10

Beginner / Machine Learning(ML), Deep Learning(DL), AI, AI Agent

5.0

(18)

Essential certification for the AI era, MS AI-900! 🚀 Did you know? ChatGPT operates exclusively on Microsoft Azure! If you want to properly utilize Microsoft Azure OpenAI, which exclusively provides the latest GPT models, now is the perfect opportunity. Grow into an Azure AI services expert through the AI-900 course and master enterprise-grade AI solutions that companies trust. Secure global official certification and enhance your competitiveness as a true AI professional!

Beginner

Machine Learning(ML), Deep Learning(DL), AI

[7-Day Complete] Pass MS AI-900 Certification in One Go

jobgreegi

$34.10

Beginner / Machine Learning(ML), Deep Learning(DL), AI, AI Agent

5.0

(18)

[Tensorflow2] Complete conquest of Python machine learning - Marathon record prediction project

nomad

Intermediate / Tensorflow, Machine Learning(ML), Keras, Computer Vision(CV)

4.1

(25)

This is a comprehensive machine learning project course that learns various useful machine learning regression and classification projects along with theory using Python and TensorFlow 2 based on Boston Marathon big data.

Intermediate

Tensorflow, Machine Learning(ML), Keras

[Tensorflow2] Complete conquest of Python machine learning - Marathon record prediction project

nomad

Intermediate / Tensorflow, Machine Learning(ML), Keras, Computer Vision(CV)

4.1

(25)