Machine Learning Training Utilities - Build Custom OCR, ASR, and Object Detection Models with TensorFlow and PyTorch

Learn to build and train machine learning models through hands-on tutorials covering optical character recognition (OCR), automatic speech recognition (ASR), handwriting recognition, and object detection using TensorFlow and PyTorch. Master custom OCR model development for CAPTCHA solving and handwritten text recognition, including sentence-level recognition with CTC loss functions. Explore PyTorch fundamentals through practical MNIST implementation and discover efficient neural network training techniques with specialized wrappers. Develop handwriting recognition systems capable of processing individual words and complete sentences. Gain expertise in real-time object detection using YOLOv8 and learn to customize training pipelines with MLTU (Machine Learning Training Utilities) for enhanced model performance and deployment.

Syllabus

Build a Custom OCR Model in TensorFlow: A Step-by-Step Tutorial
TensorFlow Step-by-Step Captcha solving tutorial with custom OCR model
Step-by-Step Handwriting Recognition Tutorial Using TensorFlow
Step-by-Step Handwritten Sentence Recognition with TensorFlow and CTC loss
Build a Custom ASR Model in TensorFlow: A Step-by-Step Tutorial
Introduction to PyTorch in a practical way with MNIST
Build and Train Neural Network with PyTorch in 15 Minutes with this Wrapper
Step-By-Step Handwriting Words Recognition With PyTorch
YOLOv8: Real-Time Object Detection Simplified
Customize YOLOv8 Object Detection training with MLTU