Ed Frey's repositories
Machine-Learning-Projects
Various projects in Linear Regression, Logistic Regression, k Nearest Neighbors, Decision Trees, Random Forests, SVM
DNN_fit_high_dim_function
a simple code using tensorflow to fit high dimensional function
F-Principle
code to show F-Principle in the DNN training
gluon-cv
Gluon CV Toolkit
Handwritten-Digit-Classification
1) Download the MNIST handwritten digit dataset. It contains 28X28 images. Flatten them into 784-dimensional binary vectors. Keep aside 20% data for testing and another 20% for validation. [1 mark] 2) Now, draw a random subset of 10 dimensions (out of 784). Based on these 10 dimensions only, build a decision tree (using library function). Maximum depth allowed: 5. Calculate accuracy of the tree on validation set. [2 mark] 3) Repeat this process for 50 random subsets like this, each of dimension 10.For each of them, build a decision tree of max. depth 5. Calculate accuracy on validation set. [2 marks] 4) Carry out weighted classification of the test set using these 50 decision trees, along with their validation accuracies as weights. Report the accuracy. [1 marks] 5) Starting with this ensemble as the initial classifier, implement Adaboost algorithm. At each stage, build a decision tree using entropy based on weighted examples as the heterogeneity measure of each node. Each tree will have maximum depth of 5. Maximum 20 iterations of Adaboost. [3 marks] 6) Using this ensemble, carry out classification on the test set and report accuracy [1 mark]
image_class
基于keras集成多种图像分类模型： VGG16、VGG19、InceptionV3、Xception、MobileNet、AlexNet、LeNet、ZF_Net、ResNet18、ResNet34、ResNet50、ResNet_101、ResNet_152、DenseNet
Inception-v4
Inception-v4, Inception - Resnet-v1 and v2 Architectures in Keras
Keras-CIFAR10
practice on CIFAR10 with Keras
Keras-famous_CNN
This repository is the implementation of several famous convolution neural network architecture with Keras. (Resnet v1, Resnet v2, Inception v1/GoogLeNet, Inception v2, Inception v3))
keras-inceptionV4
Keras Implementation of Google's Inception-V4 Architecture (includes Keras compatible pre-trained weights)
Machine-Learning-with-Python
Python code for common Machine Learning Algorithms
models
Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型）
models-1
Models and examples built with TensorFlow
Multi-label-Image-Classification-using-Tensorflow
Implementation of: 1) simple CNN for MNIST 2) Alexnet and VGG16 net(from scratch as well as using pre-trained ImageNet weights) on Pascal VOC2007 dataset
noteshrink
Convert scans of handwritten notes to beautiful, compact PDFs
Python-code-practice
Python数据分析和机器学习练习
PythonGIS
Python在GIS、RS中的实践
tensorflow_macos
TensorFlow for macOS 11.0+ accelerated using Apple's ML Compute framework.
tutorials
Tutorials on deep learning, Python, and dissipative particle dynamics
vision
Datasets, Transforms and Models specific to Computer Vision
yolo-tf2
yolo(all versions) implementation in keras and tensorflow 2.x
yolo3-tf2
这是一个yolo3-tf2的源码，可以用于训练自己的模型。
YOLO_v1_TF2
Implementation of YOLO_v1 model with TensorFlow2
yolov7
🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥