Data Science Machine Learning Data Analysis
37.3K subscribers
1.68K photos
28 videos
39 files
1.25K links
This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

Cross promotion and ads: @hussein_sheikho
Download Telegram
Get top-tier market analysis: world events meet technical trading.

I'm Michael πŸ‘‹. My team and I share our market insights daily on our Telegram channel. Over the past weekend, our strategies delivered up to +39% gains.

We will tell you everything on the channel, even for beginners.
Join the channel below! πŸ‘‡
https://t.iss.one/+9mZure1faNRkOTE8
❀1
✨ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset ✨

πŸ“– Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Training…...

🏷️ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
πŸ‘1
✨ Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection ✨

πŸ“– Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:…...

🏷️ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
✨ Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset ✨

πŸ“– Table of Contents Training YOLOv12 for Detecting Pothole Severity Using a Custom Dataset Introduction Dataset and Task Overview About the Dataset What Are We Detecting? Defining Pothole Severity Can the Pothole Severity Logic Be Improved? Configuring Your Development Environment Training…...

🏷️ #ComputerVision #DeepLearning #ObjectDetection #Tutorial #YOLO
✨ Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection ✨

πŸ“– Table of Contents Breaking the CNN Mold: YOLOv12 Brings Attention to Real-Time Object Detection The YOLO Evolution (Quick Recap) YOLOv8: Introducing the C2f Module and OBB Support YOLOv9: Programmable Gradient Information and GELAN YOLOv10: NMS-Free Training and Dual Assignments YOLOv11:…...

🏷️ #AttentionMechanisms #DeepLearning #RealTimeObjectDetection #Tutorial #YOLOSeries
✨ Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API ✨

πŸ“– Table of Contents Building a Multimodal Gradio Chatbot with Llama 3.2 Using the Ollama API What Is Gradio and Why Is It Ideal for Chatbots? The Chatbot You’ll Build Today πŸš€ What Is Ollama and the Ollama API Functionality Ollama…...

🏷️ #AIApplications #Chatbots #DeepLearning #Gradio #LargeLanguageModels #OpenSource #Tutorial
✨ NeRFs Explained: Goodbye Photogrammetry? ✨

πŸ“– Table of Contents NeRFs Explained: Goodbye Photogrammetry? How Do NeRFs Work? Block #A: We Begin with a 5D Input Block #B: The Neural Network and Its Output Block #C: Volumetric Rendering The NeRF Problem and Evolutions Summary and Next Steps…...

🏷️ #3DComputerVision #3DReconstruction #DeepLearning #NeuralNetworks #Photogrammetry #Tutorial
✨ Face detection with dlib (HOG and CNN) ✨

πŸ“– In this tutorial, you will learn how to perform face detection with the dlib library using both HOG + Linear SVM and CNNs. The dlib library is arguably one of the most utilized packages for face recognition. A Python package…...

🏷️ #dlib #FaceApplications #Tutorials
❀1
✨ Optimizing dlib shape predictor accuracy with find_min_global ✨

πŸ“– In this tutorial you will learn how to use dlib’s find_min_global function to optimize the options and hyperparameters to dlib’s shape predictor, yielding a more accurate model. A few weeks ago I published a two-part series on using dlib to…...

🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
✨ Tuning dlib shape predictor hyperparameters to balance speed, accuracy, and model size ✨

πŸ“– In this tutorial, you will learn how to optimally tune dlib’s shape predictor hyperparameters and options to obtain a shape predictor that balances speed, accuracy, and model size. Today is part two in our two-part series on training custom shape…...

🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
✨ Training a custom dlib shape predictor ✨

πŸ“– In this tutorial, you will learn how to train your own custom dlib shape predictor. You’ll then learn how to take your trained dlib shape predictor and use it to predict landmarks on input images and real-time video streams. Today…...

🏷️ #dlib #FaceApplications #FacialLandmarks #ShapePredictors #Tutorials
❀1
✨ Introduction to OpenCV AI Kit (OAK) ✨

πŸ“– Table of Contents Introduction to OpenCV AI Kit (OAK) Introduction OAK Hardware OAK-1 OAK-D Limitation OAK-FFC OAK USB Hardware Offerings OAK PoE Hardware Offerings OAK Developer Kit OAK Modules Comparison Applications on OAK Image Classifier On-Device Face Detection Face Mask…...

🏷️ #EmbeddedIoTandComputerVision #EmbeddedIoTComputerVision #OAK #Tutorials
❀1
✨ An interview with Jagadish Mahendran, 1st place winner of the OpenCV Spatial AI Competition ✨

πŸ“– In this post, I interview Jagadish Mahendran, senior Computer Vision/Artificial Intelligence (AI) engineer who recently won 1st place in the OpenCV Spatial AI Competition using the new OpenCV AI Kit (OAK). Jagadish’s winning project was a computer vision system for…...

🏷️ #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
✨ An interview with Brandon Gilles, creator of the OpenCV AI Kit (OAK) ✨

πŸ“– In this post, I interview Brandon Gilles, a longtime PyImageSearch reader, and creator of the OpenCV AI Kit (OAK), which is revolutionizing how we are performing embedded computer vision and deep learning. To celebrate the 20th anniversary of the OpenCV…...

🏷️ #DeepLearning #EmbeddedIoTandComputerVision #Interviews #OpenCVAIKit
❀1
✨ How to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning ✨

πŸ“– In today’s tutorial, you will learn how to configure your NVIDIA Jetson Nano for Computer Vision and Deep Learning with TensorFlow, Keras, TensorRT, and OpenCV. Two weeks ago, we discussed how to use my pre-configured Nano .img file β€” today,…...

🏷️ #DeepLearning #EmbeddedIoTandComputerVision #IoT #Tutorials
❀2
✨ OpenCV Eigenfaces for Face Recognition ✨

πŸ“– In this tutorial, you will learn how to implement face recognition using the Eigenfaces algorithm, OpenCV, and scikit-learn. Our previous tutorial introduced the concept of face recognition β€” detecting the presence of a face in an image/video and then subsequently…...

🏷️ #FaceApplications #OpenCVTutorials #Tutorials
❀1
✨ Face Recognition with Local Binary Patterns (LBPs) and OpenCV ✨

πŸ“– In this tutorial, you will learn how to perform face recognition using Local Binary Patterns (LBPs), OpenCV, and the cv2.face.LBPHFaceRecognizer_create function. In our previous tutorial, we discussed the fundamentals of face recognition, including: The difference between face detection and face…...

🏷️ #FaceApplications #OpenCVTutorials #Tutorials
❀1
✨ What is face recognition? ✨

πŸ“– In this tutorial, you will learn about face recognition, including: How face recognition works How face recognition is different from face detection A history of face recognition algorithms State-of-the-art algorithms used for face recognition today Next week we will start…...

🏷️ #FaceApplications
✨ Face detection tips, suggestions, and best practices ✨

πŸ“– In this tutorial, you will learn my tips, suggestions, and best practices to achieve high face detection accuracy with OpenCV and dlib. We’ve covered face detection four times on the PyImageSearch blog: Face detection with OpenCV and Haar cascades Face…...

🏷️ #FaceApplications #OpenCVTutorials #Tutorials
✨ Sharpen Your Vision: Super-Resolution of CCTV Images Using Hugging Face Diffusers ✨

πŸ“– Table of Contents Sharpen Your Vision: Super-Resolution of CCTV Images Using Hugging Face Diffusers Configuring Your Development Environment Problem Statement How Does Super-Resolution Solve This? State-of-the-Art Approaches Generative Adversarial Networks (GANs) Diffusion Models Implementing Diffus...

🏷️ #ArtificialIntelligence #ComputerVision #DeepLearning #ImageProcessing #MachineLearning #Tutorial