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TinyML

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Install / Use

/learn @thommaskevin/TinyML

About this skill

Quality Score

0/100

Category

Development & Engineering

Supported Platforms

Universal

README

TinyML

Repository

01 - Decision Tree
02 - Random Forest
03 - XGBoost Classifier
04 - GaussianNB
05 - Support Vector Machines
06 - SEFR
07 - Principal Component Analysis
08 - Binomial Logistic Regression
09 - K-means
10 - Linear Regression
11 - Gaussian Mixture Model
12 - Artificial Neural Networks (MLP)
13 - Convolutional Neural Networks (CNN)
14 - XGBoost Regression
15 - Poisson Regression
16 - K-Nearest Neighbors (KNN-Classifier)
17 - ElasticNet (ELNET)
18 - Long Short-Term Memory (LSTM)
19 - AutoEncoder
20 - Q-Learning
21 - Huber Regression
22 - Quantization Aware Training
23 - Post-Training Pruning
24 - Knowledge Distillation
25 - MicroMobileNet
26 - MultinominalNB (Text Classifier)
27 - Kolmogorov-Arnold Networks (KAN)
28 - Linear Discriminant Analysis (LDA)
29 - Radial Basis Function Networks (RBFN)
30 - Graph Convolutional Networks (GCN)
31 - Neural Additive Models (NAM)

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thommaskevin

View profile

GitHub Stars91

CategoryDevelopment

Updated19h ago

Forks22

thommaskevin/TinyML

Languages

Jupyter Notebook

Security Score

75/100

Audited on Apr 1, 2026

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