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Learn to build a real-time Automatic Number Plate Recognition system using Python, TensorFlow, and EasyOCR. Covers plate detection, OCR application, and result saving for practical implementation.
Comprehensive guide to Tensorflow Object Detection: from setup to advanced projects. Learn to build, train, and deploy models for gesture, defect, and sentiment detection using Python, JavaScript, and Raspberry Pi.
Comprehensive guide to building a face detection model using TensorFlow and Python, covering data collection, augmentation, model creation, training, and real-time testing for practical implementation.
Enhance image resolution using ESRGAN and Python. Learn to upscale images up to 4x size with this beginner-friendly tutorial covering repo cloning, model setup, and dependency installation.
Automate sales forecasting using AutoAI and Python, integrating machine learning pipelines with Excel for efficient and accurate predictions.
Learn to extract prescription medication labels using PaddleOCR and Python. Gain hands-on experience in optical character recognition, from installation to visualization, with potential applications in accessibility.
Comprehensive Python tutorial covering fundamentals, data structures, control flow, functions, OOP, modules, file handling, and math operations, with practical data science applications and projects.
Learn Python conditions and loops for data science, covering if-else statements, logical operators, loop types, and iterating through lists and dictionaries with practical applications.
Learn essential Python concepts for data science: variables, data types, lists, and dictionaries. Gain practical skills through hands-on examples and clear explanations.
Learn Python for data science: set up Jupyter Notebooks, understand its basics, write your first code, and explore Python in various environments. Perfect for beginners starting their data science journey.
Learn to build a language translation app using Python, Hugging Face Transformers, and Gradio. Covers installation, text translation with deep learning, and creating a lightweight ML app interface.
Learn to implement drowsiness detection using YOLO, PyTorch, and Python. Covers object detection, model fine-tuning, and real-time application for driver safety.
Learn to implement real-time pose estimation using MoveNet Lightning, a fast Python deep learning model. Covers installation, TFLite integration, rendering results, and OpenCV implementation.
Learn to rapidly build and evaluate a heart disease prediction model using PyCaret, a low-code ML library. Covers data loading, model training, testing, and saving in just 12 lines of code.
Learn to create a Python app for grammar correction using Gramformer and Gradio. Develop skills in deep learning, natural language processing, and app deployment for improved writing assistance.
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