Pinned Repositories
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基于SVM美女图像分类
backPropagationNN
Backpropagation neural network in python/numpy
CIFAR-10-classification-with-image-augmentation
CIFAR10 classification using CNNs including image augmentation using CV2
Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
Diabetes-Drug-Reverses-Alzheimers-Symptoms
The detailed analysis of the data, can be understood that it needs to be properly pre-processed to feed it to the predictive model. Therefore, the data is converted to a format the model best understands, and then exploratory data analysis is performed. Lot of facts has been discovered in this analysis. Later in the prediction part, there are 3 main models used. With the help of python’s well-known library package “sci-kit learn” it is easily possible to implement and execute different types of model. Initially, we use a model called Support vector classifier. This gives a decent amount of accuracy of predictions. Later the same model is optimized and cross validated. It still stays with decent accuracy rate. Secondly, used other models like linear regression, adaptive boosting, and sci-kit learn’s simple neural network called MLP – multi-layered perceptron package. All give fair amount of accuracy. Adaptive booting gives 100 percent accuracy. Since the out is binary, adaptive boosting algorithm is the most accurate one.
guofei9987.github.io
My blog
optunity
optimization routines for hyperparameter tuning
practicalAI-cn
AI实战-practicalAI 中文版
py
Repository to store sample python programs for python learning
SwarmPackagePy
Library of swarm optimization algorithms.
321HG's Repositories
321HG/-H1
A series of Jupyter notebooks showing how to load well log and petrophysical data in python.
321HG/albumentations
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
321HG/awesome-causality-algorithms
An index of algorithms for learning causality with data
321HG/captum
Model interpretability and understanding for PyTorch
321HG/caus
321HG/CloudComPy
Python wrapper for CloudCompare
321HG/crepes
Conformal regressors and predictive systems
321HG/DeepTables
DeepTables: Deep-learning Toolkit for Tabular data
321HG/difflogic
A Library for Differentiable Logic Gate Networks
321HG/DSE
Software to extract discontinuity sets from rock masses' 3D point clouds
321HG/FireflyAlgorithm
Implementation of Firefly Algorithm in Python
321HG/interesting-python
有趣、实用的Python🐍
321HG/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
321HG/ML-Papers-Explained
Explanation to key concepts in ML
321HG/MMseg
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
321HG/mplstereonet
Stereonets for matplotlib
321HG/Numerical-modeling-of-wing-crack-propagation-accounting-for-fracture-contact-mechanics
Implementation of fracture propagation
321HG/Open3D
Open3D: A Modern Library for 3D Data Processing
321HG/Open3D-ML
An extension of Open3D to address 3D Machine Learning tasks
321HG/PlotNeuralNet
Latex code for making neural networks diagrams
321HG/plotnine
A grammar of graphics for Python
321HG/py-pde
Python package for solving partial differential equations using finite differences.
321HG/PyKrige
Kriging Toolkit for Python
321HG/pyqtgraph
Fast data visualization and GUI tools for scientific / engineering applications
321HG/rulefit
Python implementation of the rulefit algorithm
321HG/skorch
A scikit-learn compatible neural network library that wraps PyTorch
321HG/statannotations
add statistical significance annotations on seaborn plots. Further development of statannot, with bugfixes, new features, and a different API.
321HG/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network
Tools to Design or Visualize Architecture of Neural Network
321HG/traj_anomal_detect
using dbscan cluster to detect anomal trajectories
321HG/YLearn
YLearn, a pun of "learn why", is a python package for causal inference