Extract Drug Labels Using Deep Learning with PaddleOCR and Python
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.
Implementing a Multi-Class CNN Image Classifier in Pytorch - Computer Vision Basics Ep. 3 CIFAR10 CNN
Learn to build a CNN image classifier using PyTorch and CIFAR10 dataset. Covers data loading, model architecture, training, and validation, with practical coding examples for computer vision enthusiasts.
Understanding Convolution Kernels for CNNs - Computer Vision Basics - What Are Convolutions?
Explore convolutional kernels in CNNs, from basic concepts to practical applications in PyTorch. Learn visualization techniques and understand their impact on computer vision tasks.
Image Classification with CIFAR 10 - Computer Vision Basics Ep. 1 Loading Data
Practical guide to image classification using CIFAR10 dataset. Learn to load data, create DataLoaders, transform images, and visualize the dataset in PyTorch for computer vision tasks.
Masked Language Modelling with Hugging Face - Microsoft Sentence Completion - Coding Tutorial
Practical guide to applying Hugging Face language models for sentence completion, covering masked language modeling, data inspection, model application, and performance evaluation.
What Is Hugging Face - Crash Course - ML Products for Beginners
Comprehensive overview of Hugging Face's ML ecosystem, covering its company background, key products, and tools for NLP and machine learning, suitable for beginners without coding.
What is Interpretable Machine Learning - ML Explainability - with Python LIME Shap Tutorial
Explore interpretable machine learning with Python, covering LIME and SHAP techniques for explainable AI. Learn why ML explainability matters and how to implement it in your projects.
Build Your First Model with PyTorch and Python - PyTorch Tutorial for Beginners
Learn to implement a Simple Linear Regression model using PyTorch, covering data exploration, model creation, tensor conversion, training, and prediction analysis in this beginner-friendly tutorial.
Create YOLO Dataset for Custom Object Detection Using OpenCV, PyTorch, and Python Tutorial
Learn to create custom datasets for YOLOv5 object detection, focusing on clothing items in images using OpenCV, PyTorch, and Python. Includes dataset preparation, format conversion, and file structure explanation.
3D Photo Inpainting Python Tutorial - Turn Any Picture Into 3D Photo with Machine Learning
Learn to create stunning 3D photos from regular images using machine learning and Python. Explore the process of 3D photo inpainting, from setup to final results, in this hands-on tutorial.
How to Create a Neural Network and Train It to Identify Doodles
Comprehensive guide to building and training neural networks from scratch, covering key concepts and practical implementation for image recognition tasks.
Complete Natural Language Processing Tutorial in Python
Comprehensive Python tutorial covering NLP fundamentals, techniques, and state-of-the-art models. Includes practical examples using popular libraries and hands-on implementation of advanced concepts.
Real-World Python Neural Nets Tutorial - Image Classification with CNN - Tensorflow & Keras
Learn to build and train a CNN for image classification using TensorFlow and Keras. Covers data preparation, model improvement, hyperparameter tuning, and practical applications in Python.
Real-World Python Machine Learning Tutorial With Scikit Learn
Comprehensive Python machine learning tutorial covering sentiment analysis using scikit-learn, from data preparation to model evaluation and optimization, with practical examples using Amazon reviews.
How to Build a Content Moderation App in Python for Analyzing Audio Files
Learn to build a Python app for audio content moderation using AssemblyAI API and Streamlit. Transcribe audio, analyze content, and create an interactive tool for efficient moderation.
Build Your First Machine Learning Model in Python
Learn to build a machine learning model in Python using scikit-learn. Covers data loading, splitting, model building with linear regression and random forest, comparison, and visualization.
Enhance Low Light Images Using Keras, Python and Weights & Biases
Learn to enhance low-light images using Zero-DCE, an unsupervised technique implemented with Python, Keras, and Weights & Biases. Explore model training, experiment tracking, and result visualization in this hands-on tutorial.
Stress Testing Qdrant - Semantic Search with 90,000 Vectors - Lightning Fast Search Microservice
Explore stress testing Qdrant for semantic search with 90,000 vectors. Learn to set up TensorFlow, generate data, and evaluate search efficiency in this hands-on tutorial.
Metaprompting with GPT-3 to Dynamically Generate Arguments
Explore advanced techniques for generating complex arguments and essays using GPT-3, including prompt chaining, metaprompting, and automated writing strategies.
Finetune GPT-3 to Write a Coherent Novel - Success! With Minor Bugs
Explore the process of using AI to write a novel, from generating summaries to creating full chapters, with insights on recursive neural networks and GPT-3 implementation.
Fine-Tune Multiple Cognitive Tasks with GPT-3 on Medical Texts and Reduce Hallucination
Learn to finetune GPT-3 for medical tasks, reduce hallucination, and improve accuracy in extracting information from patient charts and generating diagnoses.