Build a Deep Audio Classifier with Python and Tensorflow
Learn to build a deep audio classifier using Python and TensorFlow, covering data loading, preprocessing, model creation, and prediction for audio classification tasks.
Deep Fake Images and Video with SimSwap
Learn to apply face swapping technology using SimSwap model. Gain understanding of the GAN, apply it to images and videos, and explore various use cases. Includes step-by-step tutorial and final results demonstration.
Build a Deep Q&A Web App with Transformers and Anvil - Python Deep Learning App
Learn to create a deep learning Q&A web app using Python, Transformers, and Anvil. Covers model loading, app development, integration, and deployment in a hands-on tutorial.
Build a Deep Facial Recognition App - Kivy Computer Vision App with OpenCV and Tensorflow
Learn to build a deep facial recognition app using Kivy, OpenCV, and TensorFlow. Implement facial verification, create a custom layer, handle webcam input, and fine-tune the model for optimal performance.
Build a Deep Facial Recognition App - Real Time Predictions with OpenCV - Python
Learn to implement real-time facial recognition in Python using OpenCV, including setting up verification images, building a verify function, and performing recognition with webcam integration.
Build a Deep Facial Recognition App - Making Facial Recognition Predictions - Python
Learn to implement facial recognition in Python using Siamese Neural Networks, including making predictions, calculating metrics, and saving/reloading the model for real-world applications.
Build a Deep Facial Recognition App - Training a Siamese Neural Network - Python
Learn to train a Siamese Neural Network for facial recognition using Python and TensorFlow. Covers loss functions, optimizers, custom training steps, and model training implementation.
Build a Deep Facial Recognition App - Building a Siamese Neural Network - Python
Learn to build a Siamese Neural Network for facial recognition using TensorFlow, including image embedding, L1 distance layer, and model integration in a Kivy app.
Build a Deep Facial Recognition App - Collecting Data - Deep Learning Project Tutorial
Learn to build a deep facial recognition app by collecting and processing data, using OpenCV for webcam access, and preparing images for model training.
Build a Deep Facial Recognition App from Paper to Code - Deep Learning Project Tutorial
Learn to build a deep facial recognition app using TensorFlow, from setting up dependencies to creating data structures. Implement Siamese Neural Networks for one-shot image recognition in this hands-on tutorial.
Automatic Summarization Using Deep Learning - Abstractive Summarization With Pegasus
Learn to use Pegasus for automatic text summarization with Python and Transformers. Covers installation, model configuration, and summarizing Wikipedia articles, news, and scientific papers.
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.
Hugging Face Transformers - The Basics - Practical Coding Guides - NLP Models (BERT/RoBERTa)
Learn the basics of Hugging Face Transformers library, including installation, pre-defined pipelines, and implementing models in PyTorch. Explore tokenization, attention masks, and model outputs in this practical coding guide.
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.
Mastering PyTorch Tensors- The Ultimate Guide for Beginners
Comprehensive guide to PyTorch tensors: creation, types, operations, indexing, reshaping, and data handling. Essential for beginners in machine learning and deep learning projects.
Getting Started with PyTorch Lightning for Deep Learning
Explore PyTorch Lightning for easier Deep Learning projects, using Google's GoEmotions dataset to build an emotion classification model with practical coding examples.
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.
Multi-Label Classification on Unhealthy Comments - Finetuning RoBERTa with PyTorch - Coding Tutorial
Learn to finetune RoBERTa for multi-label classification of unhealthy comments using PyTorch Lightning. Practical coding guide covers data preparation, model creation, training, and evaluation.