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https://github.com/nextgencodes/dspath

Collecting DS methods in one place
https://github.com/nextgencodes/dspath

arduino data-science data-science-projects deep deep-learning deep-neural-networks gpu iot jetson machine-learning machine-learning-algorithms machine-learning-models nvidia raspberrypi robotics

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Collecting DS methods in one place

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README

        

# HyperEscape - Data Science Tutorials

Welcome to Robo.Run.Place, your comprehensive resource for learning data science and machine learning! This repository provides links to our in-depth tutorials covering a wide range of topics, from fundamental algorithms to advanced techniques. Whether you're a beginner or an experienced practitioner, you'll find valuable learning materials here.

Our website ([https://robo.run.place](https://robo.run.place)) offers a structured approach to learning, with clear explanations, practical examples, and hands-on exercises.

## Course Overview

Here's a breakdown of the topics we cover:

### Classification Algorithms
- [Decision Tree](https://robo.run.place/courses/classification/decision-tree/)
- [Decision Stump](https://robo.run.place/courses/classification/decision-stump/)
- [Naive Bayes](https://robo.run.place/courses/classification/naive-bayes/)
- [Gaussian Naive Bayes](https://robo.run.place/courses/classification/gaussian-nb/)
- [Bernoulli Naive Bayes](https://robo.run.place/courses/classification/bernoulli-nb/)
- [Multinomial Naive Bayes](https://robo.run.place/courses/classification/multinomial-nb/)
- [K Nearest Neighbours (KNN)](https://robo.run.place/courses/classification/knn/)
- [Support Vector Machine (SVM)](https://robo.run.place/courses/classification/svm/)
- [Linear Support Vector Classifier (SVC)](https://robo.run.place/courses/classification/svc/)
- [NuSVC](https://robo.run.place/courses/classification/nusvc/)
- [Stochastic Gradient Descent Classifier (SGD)](https://robo.run.place/courses/classification/sgd/)
- [Bayesian Network](https://robo.run.place/courses/classification/bayesian-network/)
- [Logistic Regression](https://robo.run.place/courses/classification/logistic/)
- [Zero Rule (ZeroR)](https://robo.run.place/courses/classification/zeror/)
- [One Rule (OneR)](https://robo.run.place/courses/classification/oner/)
- [Linear Discriminant Analysis (LDA)](https://robo.run.place/courses/classification/lda/)
- [Quadratic Discriminant Analysis (QDA)](https://robo.run.place/courses/classification/qda/)
- [Fisher's Linear Discriminant](https://robo.run.place/courses/classification/fsd/)

### Regression Analysis
- [Linear Regression](https://robo.run.place/courses/regression/lr/)
- [Polynomial Regression](https://robo.run.place/courses/regression/polyr/)
- [Poisson Regression](https://robo.run.place/courses/regression/poissonr/)
- [Ordinary Least Squares (OLS) Regression](https://robo.run.place/courses/regression/olsr/)
- [Ordinal Regression](https://robo.run.place/courses/regression/ordinalr/)
- [Support Vector Regression](https://robo.run.place/courses/regression/svr/)
- [Gradient Descent Regression](https://robo.run.place/courses/regression/gradientdescentr/)
- [Stepwise Regression](https://robo.run.place/courses/regression/stepwiser/)
- [Lasso Regression (Least absoulute selection and shrinkage operator)](https://robo.run.place/courses/regression/lassor/)
- [Ridge Regression (L2)](https://robo.run.place/courses/regression/ridger/)
- [Elastic Net Regression](https://robo.run.place/courses/regression/elasticnetr/)
- [Bayesian Linear Regression](https://robo.run.place/courses/regression/bayesianlr/)
- [Least-Angled Regression (LARS)](https://robo.run.place/courses/regression/lars/)
- [Neural Network Regression](https://robo.run.place/courses/regression/nnr/)
- [Locally Estimated Scatterplot Smoothing (LOESS)](https://robo.run.place/courses/regression/loessr/)
- [Multivariate Adaptive Regression Splines (MARS)](https://robo.run.place/courses/regression/mars/)
- [Locally Weighted Regression (LWL)](https://robo.run.place/courses/regression/lwlr/)
- [Quantile Regression](https://robo.run.place/courses/regression/quantiler/)
- [Principal Component Regression (PCR)](https://robo.run.place/courses/regression/pcr/)
- [Partial Least Squares Regression](https://robo.run.place/courses/regression/plsr/)

### Neural Networks
- [Perceptron](https://robo.run.place/courses/nn/perceptron/)
- [Multilayer Perceptron (MLP)](https://robo.run.place/courses/nn/mlp/)
- [Recurrent Neural Network (RNN)](https://robo.run.place/courses/nn/rnn/)
- [Convolutional Neural Network (CNN)](https://robo.run.place/courses/nn/cnn/)
- [Deep Belief Network (DBN)](https://robo.run.place/courses/nn/dbn/)
- [Hopfield Networks](https://robo.run.place/courses/nn/hopfield/)
- [Learning Vector Quantization (LVQ)](https://robo.run.place/courses/nn/lvq/)
- [Stacked Autoencoder](https://robo.run.place/courses/nn/stackedencoder/)
- [Boltzmann Machine](https://robo.run.place/courses/nn/boltzmann/)
- [Restricted Boltzmann Machine (RBM)](https://robo.run.place/courses/nn/rbm/)
- [Generative Adversarial Networks (GANs)](https://robo.run.place/courses/nn/gan/)
- [Variational Autoencoder (VARs)](https://robo.run.place/courses/nn/var/)
- [Long Short-Term Memory](https://robo.run.place/courses/nn/lstm/)

### Anomaly Detection
- [Isolation Forest](https://robo.run.place/courses/anomaly/isolation-forest/)
- [Once Class SVM](https://robo.run.place/courses/anomaly/OcSVM/)
- [PCA-Based Anomaly Detection](https://robo.run.place/courses/anomaly/pca-anomaly/)
- [Fast-MCD](https://robo.run.place/courses/anomaly/fast-mcd/)
- [Local Outlier Factor (LOF)](https://robo.run.place/courses/anomaly/lof/)

### Dimensionality Reduction
- [Singular Value Decomposition (SVD)](https://robo.run.place/courses/dimensionality/svd/)
- [Forward Feature Selection](https://robo.run.place/courses/dimensionality/forwardfeatures/)
- [Backward Feature Elemination](https://robo.run.place/courses/dimensionality/backward-feature/)
- [Subset Selection](https://robo.run.place/courses/dimensionality/subsetselection/)
- [Principal Component Analysis (PCA)](https://robo.run.place/courses/dimensionality/pca)
- [Partial Least Squares Regression (PLSR)](https://robo.run.place/courses/dimensionality/plsr/)
- [Latent Dirichlet Analysis (LDA)](https://robo.run.place/courses/dimensionality/lda/)
- [Regularized Discriminant Analysis (RDA)](https://robo.run.place/courses/dimensionality/rda/)
- [t-Distributed Stochastic Neighbor Embedding (t-SNE)](https://robo.run.place/courses/dimensionality/tsne/)
- [Factor Analysis](https://robo.run.place/courses/dimensionality/factor-analysis/)
- [Multidimensional Scaling (MDS)](https://robo.run.place/courses/dimensionality/mds/)
- [AutoEncoder](https://robo.run.place/courses/dimensionality/autoencoder/)
- [Independent Component Analysis (ICA)](https://robo.run.place/courses/dimensionality/ica/)
- [Isomap](https://robo.run.place/courses/dimensionality/isomap/)
- [Local Linear Embedding (LLE)](https://robo.run.place/courses/dimensionality/lle/)
- [Locality-Sensitive Hashing](https://robo.run.place/courses/dimensionality/localitysensitive/)
- [Sammon Mapping](https://robo.run.place/courses/dimensionality/sammon/)

### Ensemble
- [Random Forest](https://robo.run.place/courses/ensemble/random-forest/)
- [Bagging (Bootstrap Aggregation)](https://robo.run.place/courses/ensemble/bagging/)
- [AdaBoost](https://robo.run.place/courses/ensemble/adaboost/)
- [Gradient Boosting](https://robo.run.place/courses/ensemble/gradient-boosting/)
- [Gradient Boosted Regression Trees](https://robo.run.place/courses/ensemble/gradient-boosting-tree)
- [XGBoost (Extreme Gradient Boosting)](https://robo.run.place/courses/ensemble/xgboost/)
- [Voting Classifier](https://robo.run.place/courses/ensemble/voting-classifier/)
- [Extremely Randomized Trees](https://robo.run.place/courses/ensemble/ert/)
- [Boosted Decision Tree](https://robo.run.place/courses/ensemble/boosteddt/)
- [Category Boosting (CatBoost)](https://robo.run.place/courses/ensemble/category-boosting/)
- [Stacked Generalization (Stacking)](https://robo.run.place/courses/ensemble/stacking/)

### Clustering
- [K-Means Clustering](https://robo.run.place/courses/clustering/kmeans/)
- [K-Medians Clustering](https://robo.run.place/courses/clustering/kmedian/)
- [Mean Shift Clustering](https://robo.run.place/courses/clustering/meanshift/)
- [K-Modes Clustering](https://robo.run.place/courses/clustering/kmodes/)
- [Fuzzy K-Modes](https://robo.run.place/courses/clustering/fuzzy-kmodes/)
- [Fuzzy C-Means](https://robo.run.place/courses/clustering/fuzzy-cmeans/)
- [Mini Batch K-Means Clustering](https://robo.run.place/courses/clustering/minibatch-kmeans/)
- [Hierarchical Clustering](https://robo.run.place/courses/clustering/hierarchical/)
- [Expectation Maximization](https://robo.run.place/courses/clustering/expectation-max/)
- [DBSCAN](https://robo.run.place/courses/clustering/dbscan/)
- [Minimum Spanning Trees](https://robo.run.place/courses/clustering/minimum-spantree/)
- [Quality Threshold](https://robo.run.place/courses/clustering/quality-threshold/)
- [Gaussian Mixture Model (GMM)](https://robo.run.place/courses/clustering/gmm/)
- [Spectral Clustering](https://robo.run.place/courses/clustering/spectral-clustering/)

### Association Rule Learning
- [Apriori](https://robo.run.place/courses/association/apriori/)
- [Eclat](https://robo.run.place/courses/association/eclat/)

### Regularization
- [LASSO Regularization](https://robo.run.place/courses/regularization/lasso/)
- [Ridge Regularization](https://robo.run.place/courses/regularization/ridge/)
- [Elastic Net Regularization](https://robo.run.place/courses/regularization/elastic-net/)

## Get Started

Visit our website today to start learning: [https://robo.run.place](https://robo.run.place)

We are constantly updating our content with new tutorials and resources. Stay tuned for more!

## Contributing

If you have any suggestions for new content, corrections, or improvements, feel free to create an issue or submit a pull request. We welcome contributions from the community.