AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
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Updated
Mar 4, 2024 - Python
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
Plain python implementations of basic machine learning algorithms
Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web
gesture recognition toolkit
A curated list of Best Artificial Intelligence Resources
Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA
Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
文本聚类(Kmeans、DBSCAN、LDA、Single-pass)
This repository contains the code which can recognise the alphabets in Indian sign language for blind using opencv and tensorflow.
The full collection of Jupyter Notebook labs from Andrew Ng's new Machine Learning Specialization.
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Different clustering approaches applied on different problemsets
An approach to document exploration using Machine Learning. Let's cluster similar research articles together to make it easier for health professionals and researchers to find relevant research articles.
A practical guide to topic mining and interactive visualizations
Dynamically get the suggested clusters in the data for unsupervised learning.
Course Material for Artificial Intelligence and Machine Learning - Unit 2 @ Computer Science Dept, Sapienza
KMeans for big data using preconditioning and sparsification, Matlab implementation. Aka k-means
This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.
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