📄️ Vector Databases for AI Applications
An introduction to Weaviate DB for end-to-end AI applications.
📄️ DLIB Face Recognition
Detect faces in images and compare their feature vector to known entities
📄️ Audio Classification with Computer Vision
Training an YOLOv8 Classifier to Identify Audio Files
📄️ CVAT Semi-automatic and Automatic Annotation
CVAT supports supervised machine learning tasks pertaining to object detection, image classification, image segmentation and 3D data annotation.
📄️ Computer Vision Annotation Tool (CVAT) Introduction
CVAT supports supervised machine learning tasks pertaining to object detection, image classification, image segmentation and 3D data annotation.
📄️ YOLOv8 Nightshift
Training an YOLOv8 Object Tracker for Day/Night Cameras
📄️ YOLOv8 License Plate Detection
Using the YOLOv8 Object Tracker in Combination with EasyOCR
📄️ Scikit-Learn ML Model Explainability
SHAP is a game theoretic approach to explain the output of any machine learning model.
📄️ Using Tensorflow Models in OpenCV
Using Tensorflow models in OpenCV to perform semantic segmentations on images using the Mask-RCNN model.
📄️ YOLOv8 Image Classifier
I-know-flowers Image Classifier YOLOv8 Model Comparison
📄️ Detectron Object Detection with OpenImages Dataset (WIP)
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
📄️ Instance Segmentation with PyTorch (Mask RCNN)
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
📄️ Image Segmentation with PyTorch (Faster RCNN)
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
📄️ Image Segmentation with PyTorch (RCNN)
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
📄️ Image Segmentation with PyTorch
Food item segmentation from images of the Tray Food Segmentation dataset
📄️ Containerized PyTorch Dev Workflow
Develop your PyTorch models inside the official PyTorch container image.
📄️ Tensorflow Image Classifier - Model Evaluation
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - Xception
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - ViT
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - NASNetMobile
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - MobileNetV3Small
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - MobileNetV3Large
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - MobileNetV2
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - InceptionV3
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - EfficientNetV2S
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - EfficientNetV2B0
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - Data-efficient Image Transformers
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - Data Pre-processing
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow Image Classifier - Introduction
Blue print image classifier using Tensorflow and Keras Applications pre-trained models
📄️ Tensorflow VITs
ViT models apply the Transformer architecture with self-attention to sequences of image patches, without using convolution layers.
📄️ Human Emotion Detection with Tensorflow
Create a TF Image Classifier that can distinguish between different human emotion based on portrait photos.
📄️ Working with ONNX Models
Open Neural Network Exchange (ONNX)
📄️ Introduction to Caffe2
Deep Learning Framework with Python for flexibility and C++ for speed.
📄️ SQL in Data Science - Machine Learning
Cheat Sheet using Psycopg2 to interact with PostgreSQL Databases
📄️ SQL in Data Science - Slightly more Advanced Queries
Cheat Sheet using Psycopg2 to interact with PostgreSQL Databases
📄️ SQL in Data Science - The Basics using Python
Cheat Sheet using Psycopg2 to interact with PostgreSQL Databases
📄️ Detection of Exoplanets using Transit Photometry
Exoplanets are the planets found outside of the solar system. When a planet passes in front of a star, the brightness of that star as observed by us becomes dimmer depending on the size of the planet. The data we observe will show a dip in flux if a planet is transiting the star we are observing.
📄️ (Re) Introduction to Tensorflow Natural Language Processing
Using Tensorflow to classify Disaster Tweet.
📄️ 3D Image Classification
Learn how to train a 3D convolutional neural network (3D CNN) to predict presence of pneumonia.
📄️ Dimensionality Reduction for Image Segmentation
Use Manifold Learning and the LD Analysis to Visualize Image Datasets.
📄️ Fisher Linear Discriminant Analysis (LDA)
LDA is a widely used dimensionality reduction technique built on Fisher’s linear discriminant.
📄️ Isometric Mapping (ISOMAP)
Non-linear dimensionality reduction through Isometric Mapping
📄️ Multidimensional Scaling (MDS)
Multidimensional Scaling is a family of statistical methods that focus on creating mappings of items based on distance.
📄️ tStochastic Neighbor Embedding (t-SNE)
t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map.
📄️ Locally Linear Embedding (LLE)
LLE is an unsupervised learning algorithm that computes low dimensional, neighborhood preserving embeddings of high dimensional data.
📄️ Principal Component Analysis (PCA)
To aid visualization of the structure of a dataset, the dimension must be reduced in some way.
📄️ Tensorflow 2 - Unsupervised Learning
Generative Adverserial Networks for Image Data Generation
📄️ Tensorflow 2 - Unsupervised Learning
Use Autoencoders to Increase Feature Resolution
📄️ Tensorflow 2 - Unsupervised Learning
Use Autoencoders to Reduce Dimensionality and Feature Discovery
📄️ Tensorflow 2 - Transfer Learning
Scale a pre-trained model to fit your needs
📄️ Tensorflow 2 - Transfer Learning
Fine-tuning Pre-trained Models
📄️ Tensorflow 2 - Transfer Learning
Using a Pre-trained Model to Extract Features
📄️ Tensorflow 2 - Convolutional Neural Networks
Computer Vision for Multiclass Image Classifications
📄️ Tensorflow 2 - Convolutional Neural Networks
Computer Vision for Binary Image Classifications
🗃️ Tensorflow 2 - Neural Network Classifications
1 items
📄️ Tensorflow 2 - Neural Network Classification
Model Evaluation and Performance Improvement
📄️ Tensorflow 2 - Neural Network Classification
Working with a non-linear dataset and activation functions
📄️ Tensorflow 2 - Neural Network Regression
Data pre-processing - normalization and feature-scaling
📄️ Tensorflow 2 - Neural Network Regression
Working with the medical cost dataset
📄️ Tensorflow 2 - Neural Network Regression
Optimizing model performance
📄️ Tensorflow 2 - Neural Network Regression
Visualizing Models and Evaluating Model Performance
📄️ Tensorflow 2 - Neural Network Regression
Building a Regression Model and Improving it's Performance
📄️ Tensorflow 2 - An (Re)Introduction 2023 (3)
Matrix multiplications, Squeeze, One-hot and Numpy
📄️ Tensorflow 2 - An (Re)Introduction 2023 (2)
Tensor Indexing, Expanding and Manipulations
📄️ Tensorflow 2 - An (Re)Introduction 2023
Tensor Constants, Variables and Attributes
📄️ Keras for Tensorflow - VGG16 Network Architecture
An example convolutional neural network is the VGG16 Architecture.
📄️ Keras for Tensorflow - Recurrent Neural Networks
Recurrent Neural Networks are widely used to work with sequence data such as time series or natural language.
📄️ Keras for Tensorflow - Convolutional Neural Networks
Convolutional Neural Networks are ideal for Computer Vision tasks.
📄️ Keras for Tensorflow - Artificial Neural Networks
Building a deep neural network using the MNIST dataset.
📄️ YOLOv8 with AS-One
A Modular Libary for YOLO Object Detection and Object Tracking.
📄️ Keras for Tensorflow - An (Re)Introduction 2023
Keras is built on top of TensorFlow 2 and provides an API designed for human beings.
📄️ SciKit Wine Quality
Predicting Wine Quality with Several Classification Techniques using SciKit Learn.
📄️ OpenCV Count My Money
Differentiate Objects based on their Contour and Colour with cvZone.
📄️ YOLOv7 to Tensorflow
Converting a YOLOv7 PyTorch Model to Tensorflow (Lite)
📄️ YOLOv7 Label Conversion
Transferring PASCAL VOC labels to the YOLO format
📄️ YOLOv7 Training with Custom Data
Use your Custom Dataset to train YOLOv7
📄️ MiDaS Depth Vision
MiDaS computes relative inverse depth from a single image.
📄️ YOLOv7 Introduction
Getting started with object detection in YOLOv7
📄️ Recurrent Neural Networks
Generate text using a character-based RNN
📄️ Deep Convolutional Generative Adversarial Network
Use Adversarial Networks to generate Images
📄️ Tensorflow Downsampling
Using Representation Learning to Downsample Images
📄️ Tensorflow Deep Dream
DeepDream is an experiment that visualizes the patterns learned by a neural network.
📄️ Tensorflow Representation Learning
Build a Denoising Autoencoder in Tensorflow using the mnist Digits Dataset
📄️ Tensorflow Hub
TensorFlow Hub is a repository of trained machine learning models.
📄️ Tensorflow Transfer Learning
Transfer learning is a machine learning technique in which intelligence from a base ann is being transferred to a new network as a starting point.
📄️ Tensorflow Image Classification
The CIFAR-10 is a labeled subset of the 80 million tiny images dataset that can be directly downloaded using Keras.
📄️ Breast Histopathology Image Segmentation Part 6
Running Predictions
📄️ Breast Histopathology Image Segmentation Part 5
Evaluate the performance of your trained model
📄️ Breast Histopathology Image Segmentation Part 4
Train our model to fit the dataset
📄️ Breast Histopathology Image Segmentation Part 3
Model creation based on a pre-trained and a custom model
📄️ Breast Histopathology Image Segmentation Part 2
Balancing skewed datasets and data augmentation
📄️ Breast Histopathology Image Segmentation Part 1
Data Inspection and Pre-processing
📄️ Deep Docker on Arch
The NVIDIA Container Toolkit run GPU accelerated Docker containers
📄️ Face Restoration with GFPGAN
Victoria Harbour, Hongkong
📄️ Super Resolution with Real-ESRGAN
Victoria Harbour, Hongkong
📄️ Super Resolution with ESRGAN
Victoria Harbour, Hongkong
📄️ Deep Audio
Deep Audio Classifier with Tensorflow
📄️ Yolo App - YOLOv5 Data Preparation
Shenzhen, China
📄️ Yolo App - Flask Web Application
Shenzhen, China
📄️ Yolo App - Tesseract Optical Character Recognition
Shenzhen, China
📄️ Yolo App - Pipeline Predictions
Shenzhen, China
📄️ Yolo App - Train a Model with Tensorflow
Shenzhen, China
📄️ Yolo App - Data Collection
Shenzhen, China
📄️ OpenCV Optical Flow Algorithm for Object Tracking
Shenzhen, China
📄️ OpenCV CAMshift Algorithm for Object Tracking
Shenzhen, China
📄️ OpenCV Meanshift Algorithm for Object Tracking
Shenzhen, China
📄️ OpenCV Object Detection and Tracking
Shenzhen, China
📄️ OpenCV Object Tracking
Shenzhen, China
📄️ OpenCV Face Detection and Privacy
Shenzhen, China
📄️ OpenCV Image Objects
Shenzhen, China
📄️ OpenCV Image Operations
Shenzhen, China
📄️ OpenCV, Streams and Video Files
Shenzhen, China
📄️ OpenCV and Images
Shenzhen, China
📄️ Introduction into FB Prophet
Shenzhen, China
📄️ Tensorflow.js React App
Mong Kok, Hongkong
📄️ Tensorflow2 Model Zoo
Mong Kok, Hongkong
📄️ Tensorflow2 Crash Course - Part V
Mong Kok, Hongkong
📄️ Tensorflow2 Crash Course - Part IV
Mong Kok, Hongkong
📄️ Tensorflow2 Crash Course - Part III
Mong Kok, Hongkong
📄️ Tensorflow2 Crash Course - Part II
Mong Kok, Hongkong
🗃️ Tensorflow Crash Course - Part I
1 items
📄️ OpenCV Crash Course Part II
Shenzhen, China
📄️ OpenCV Crash Course Part I
Shenzhen, China
📄️ License Plate Recognition with YOLOv4, OpenCV and Tesseract
Shenzhen, China
📄️ Installing YOLOv4 with Anaconda
Shenzhen, China
📄️ Streamlit user interface for openCV/Mediapipe face mesh app
Victoria Harbour, Hongkong
📄️ spaCy NER Predictions
Victoria Harbour, Hongkong
📄️ spaCy NER on Arch Linux
Victoria Harbour, Hongkong
📄️ Introduction to Keras
Shanghai, China
📄️ Tesseract OCR on Arch Linux
Victoria Harbour, Hongkong
📄️ Introduction to TensorFlow 2 Beta
Shanghai, China
📄️ Machine Learning with SciKit Learn
Shenzhen, China