Reorganized directories by language and updated README files

mlpack · Apr 17, 2024 · 31355ba · 31355ba
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diff --git a/airbnb_price_prediction_regression/README.md b/airbnb_price_prediction_regression/README.md
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+# Airbnb Price Prediction with Regression
+
+This repository contains machine learning examples for predicting Airbnb prices using regression techniques.
+
+## Directories
+- `python`: Contains Python examples.
+
+## Files
+- `python/airbnb_price_prediction_regression_py.ipynb`: Jupyter notebook for Airbnb price prediction using regression in Python.
+
+Feel free to explore the notebook and learn about implementing regression techniques for predicting Airbnb prices.
diff --git a/...rbnb_price_prediction_regression_py.ipynb → ...rbnb_price_prediction_regression_py.ipynb b/...rbnb_price_prediction_regression_py.ipynb → ...rbnb_price_prediction_regression_py.ipynb
diff --git a/avocado_price_prediction_with_linear_regression/README.md b/avocado_price_prediction_with_linear_regression/README.md
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+# mlpack Examples: Avocado Price Prediction with Linear Regression
+
+This repository contains machine learning examples using mlpack for predicting avocado prices using linear regression in both Python and C++.
+
+## Directories
+- `python`: Contains Python examples.
+- `cpp`: Contains C++ examples.
+
+## Files
+- `python/avocado_price_prediction_with_lr_py.ipynb`: Jupyter notebook for avocado price prediction using linear regression in Python.
+- `cpp/avocado_price_prediction_with_lr_cpp.ipynb`: Jupyter notebook for avocado price prediction using linear regression in C++.
+
+Feel free to explore the notebooks and learn about implementing linear regression for avocado price prediction using mlpack.
diff --git a/...vocado_price_prediction_with_lr_cpp.ipynb → ...vocado_price_prediction_with_lr_cpp.ipynb b/...vocado_price_prediction_with_lr_cpp.ipynb → ...vocado_price_prediction_with_lr_cpp.ipynb
diff --git a/...avocado_price_prediction_with_lr_py.ipynb → ...avocado_price_prediction_with_lr_py.ipynb b/...avocado_price_prediction_with_lr_py.ipynb → ...avocado_price_prediction_with_lr_py.ipynb
diff --git a/breast_cancer_wisconsin_transformation_with_pca/README.md b/breast_cancer_wisconsin_transformation_with_pca/README.md
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+# Breast Cancer Wisconsin Transformation with PCA
+
+This directory contains machine learning examples focusing on breast cancer Wisconsin transformation using Principal Component Analysis (PCA) in both Python and C++.
+
+## Directories
+- `cpp`: Contains C++ examples.
+- `py`: Contains Python examples.
+
+## Files
+- `cpp/breast-cancer-wisconsin-pca-cpp.ipynb`: C++ notebook for breast cancer Wisconsin transformation with PCA.
+- `py/breast-cancer-wisconsin-pca-py.ipynb`: Python notebook for breast cancer Wisconsin transformation with PCA.
+
+Explore the notebooks in the respective directories to learn about implementing PCA for breast cancer data transformation in Python and C++.
diff --git a/...pca/breast-cancer-wisconsin-pca-cpp.ipynb → ...cpp/breast-cancer-wisconsin-pca-cpp.ipynb b/...pca/breast-cancer-wisconsin-pca-cpp.ipynb → ...cpp/breast-cancer-wisconsin-pca-cpp.ipynb
diff --git a/..._pca/breast-cancer-wisconsin-pca-py.ipynb → ...thon/breast-cancer-wisconsin-pca-py.ipynb b/..._pca/breast-cancer-wisconsin-pca-py.ipynb → ...thon/breast-cancer-wisconsin-pca-py.ipynb
diff --git a/cifar10_cnn/README.md b/cifar10_cnn/README.md
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+# CIFAR-10 Classification with Convolutional Neural Networks
+
+This directory contains machine learning examples focusing on classifying CIFAR-10 images using Convolutional Neural Networks (CNN).
+
+## Directories
+- `images`: Contains image assets used in the notebooks.
+- `cpp`: Contains C++ implementations.
+- `py`: Contains Python implementations.
+
+## Files
+- `cpp/cifar10_eval.cpp`: C++ implementation for evaluating CIFAR-10 image classification using CNN.
+- `cpp/cifar_train.cpp`: C++ implementation for training CIFAR-10 image classification model using CNN.
+- `py/cifar10_eval.ipynb`: Notebook for evaluating CIFAR-10 image classification using CNN in Python.
+
+Explore the notebooks and code files to learn about implementing CNN for CIFAR-10 image classification in Python and C++.
diff --git a/cifar10_cnn/Makefile → cifar10_cnn/cpp/Makefile b/cifar10_cnn/Makefile → cifar10_cnn/cpp/Makefile
diff --git a/cifar10_cnn/cifar_eval.cpp → cifar10_cnn/cpp/cifar_eval.cpp b/cifar10_cnn/cifar_eval.cpp → cifar10_cnn/cpp/cifar_eval.cpp
diff --git a/cifar10_cnn/cifar_train.cpp → cifar10_cnn/cpp/cifar_train.cpp b/cifar10_cnn/cifar_train.cpp → cifar10_cnn/cpp/cifar_train.cpp
diff --git a/cifar10_cnn/periodic_save.hpp → cifar10_cnn/cpp/periodic_save.hpp b/cifar10_cnn/periodic_save.hpp → cifar10_cnn/cpp/periodic_save.hpp
diff --git a/cifar10_cnn/notebook_ims/2_layer_conv.png → ..._cnn/images/notebook_ims/2_layer_conv.png b/cifar10_cnn/notebook_ims/2_layer_conv.png → ..._cnn/images/notebook_ims/2_layer_conv.png
diff --git a/cifar10_cnn/notebook_ims/cifar_data.png → ...10_cnn/images/notebook_ims/cifar_data.png b/cifar10_cnn/notebook_ims/cifar_data.png → ...10_cnn/images/notebook_ims/cifar_data.png
diff --git a/cifar10_cnn/cifar10_eval.ipynb → cifar10_cnn/python/cifar10_eval.ipynb b/cifar10_cnn/cifar10_eval.ipynb → cifar10_cnn/python/cifar10_eval.ipynb
diff --git a/cifar10_transformation_with_pca/README.md b/cifar10_transformation_with_pca/README.md
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+# CIFAR-10 Transformation with PCA
+
+This directory contains machine learning examples focusing on transforming CIFAR-10 images using Principal Component Analysis (PCA).
+
+## Directories
+- `images`: Contains image assets used in the notebooks.
+- `cpp`: Contains C++ implementations.
+- `py`: Contains Python implementations.
+
+## Files
+- `cpp/cifar-10-pca-cpp.ipynb`: Notebook demonstrating PCA transformation on CIFAR-10 images using C++.
+- `py/cifar-10-pca-py.ipynb`: Notebook showcasing PCA transformation on CIFAR-10 images using Python.
+
+Explore the notebooks and code files to learn about implementing PCA for transforming CIFAR-10 images in Python and C++.
diff --git a/...formation_with_pca/cifar-10-pca-cpp.ipynb → ...ation_with_pca/cpp/cifar-10-pca-cpp.ipynb b/...formation_with_pca/cifar-10-pca-cpp.ipynb → ...ation_with_pca/cpp/cifar-10-pca-cpp.ipynb
diff --git a/...sformation_with_pca/cifar-10-pca-py.ipynb → ...ion_with_pca/python/cifar-10-pca-py.ipynb b/...sformation_with_pca/cifar-10-pca-py.ipynb → ...ion_with_pca/python/cifar-10-pca-py.ipynb
diff --git a/contact_tracing_clustering_with_dbscan/README.md b/contact_tracing_clustering_with_dbscan/README.md
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+# Contact Tracing Clustering with DBSCAN using mlpack
+
+This directory contains machine learning examples focusing on clustering contact tracing data using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) with mlpack, a fast, scalable machine learning library.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+
+## Files
+- `cpp/contact-tracing-dbscan-cpp.ipynb`: Notebook demonstrating contact tracing clustering using DBSCAN with mlpack in C++.
+
+Explore the notebook to learn about implementing DBSCAN for clustering contact tracing data in C++ with mlpack.
diff --git a/...h_dbscan/contact-tracing-dbscan-cpp.ipynb → ...scan/cpp/contact-tracing-dbscan-cpp.ipynb b/...h_dbscan/contact-tracing-dbscan-cpp.ipynb → ...scan/cpp/contact-tracing-dbscan-cpp.ipynb
diff --git a/customer_personality_clustering/README.md b/customer_personality_clustering/README.md
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+# Customer Personality Clustering
+
+This directory contains machine learning examples focusing on clustering customer personalities based on various features.
+
+## Directories
+- `python`: Contains Python implementations.
+
+## Files
+- `python/customer_personality_clustering_py.ipynb`: Notebook showcasing customer personality clustering using Python.
+
+Explore the notebook and code files to learn about clustering customer personalities based on their features.
diff --git a/.../customer_personality_clustering_py.ipynb → .../customer_personality_clustering_py.ipynb b/.../customer_personality_clustering_py.ipynb → .../customer_personality_clustering_py.ipynb
diff --git a/dominant-colors-with-kmeans/README.md b/dominant-colors-with-kmeans/README.md
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+# Dominant Colors Extraction with K-Means using mlpack
+
+This directory contains a machine learning example focusing on extracting dominant colors from images using K-Means clustering with mlpack, a fast, scalable machine learning library.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+
+## Files
+- `cpp/dominant-colors-kmeans-cpp.ipynb`: Notebook demonstrating dominant colors extraction using K-Means with mlpack in C++.
+
+Explore the notebook to learn about implementing K-Means for extracting dominant colors from images in C++ with mlpack.
diff --git a/...h-kmeans/dominant-colors-kmeans-cpp.ipynb → ...eans/cpp/dominant-colors-kmeans-cpp.ipynb b/...h-kmeans/dominant-colors-kmeans-cpp.ipynb → ...eans/cpp/dominant-colors-kmeans-cpp.ipynb
diff --git a/forest_covertype_prediction_with_random_forests/README.md b/forest_covertype_prediction_with_random_forests/README.md
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+# Forest Covertype Prediction with Random Forests
+
+This directory contains machine learning examples focusing on predicting forest covertype using random forests in various programming languages.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `go`: Contains Go implementations.
+- `jl`: Contains Julia implementations.
+- `py`: Contains Python implementations.
+
+## Files
+- `cpp/covertype-rf-cpp.ipynb`: Notebook demonstrating forest covertype prediction using random forests in C++.
+- `go/covertype-rf-go.ipynb`: Notebook illustrating forest covertype prediction using random forests in Go.
+- `jl/covertype-rf-jl.ipynb`: Notebook demonstrating forest covertype prediction using random forests in Julia.
+- `py/covertype-rf-py.ipynb`: Notebook showcasing forest covertype prediction using random forests in Python.
+
+Explore the notebooks to learn about implementing random forests for predicting forest covertype across different programming languages.
diff --git a/...ith_random_forests/covertype-rf-cpp.ipynb → ...random_forests/cpp/covertype-rf-cpp.ipynb b/...ith_random_forests/covertype-rf-cpp.ipynb → ...random_forests/cpp/covertype-rf-cpp.ipynb
diff --git a/...with_random_forests/covertype-rf-go.ipynb → ...h_random_forests/go/covertype-rf-go.ipynb b/...with_random_forests/covertype-rf-go.ipynb → ...h_random_forests/go/covertype-rf-go.ipynb
diff --git a/...with_random_forests/covertype-rf-jl.ipynb → ...h_random_forests/jl/covertype-rf-jl.ipynb b/...with_random_forests/covertype-rf-jl.ipynb → ...h_random_forests/jl/covertype-rf-jl.ipynb
diff --git a/...with_random_forests/covertype-rf-py.ipynb → ...ndom_forests/python/covertype-rf-py.ipynb b/...with_random_forests/covertype-rf-py.ipynb → ...ndom_forests/python/covertype-rf-py.ipynb
diff --git a/graduate_admission_classification_with_Adaboost/README.md b/graduate_admission_classification_with_Adaboost/README.md
@@ -0,0 +1,13 @@
+# Graduate Admission Classification with AdaBoost
+
+This directory contains machine learning examples focusing on classifying graduate admission using AdaBoost algorithm in different programming languages.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `py`: Contains Python implementations.
+
+## Files
+- `cpp/graduate-admission-classification-with-adaboost-cpp.ipynb`: Notebook demonstrating graduate admission classification using AdaBoost in C++.
+- `py/graduate-admission-classification-with-adaboost-py.ipynb`: Notebook showcasing graduate admission classification using AdaBoost in Python.
+
+Explore the notebooks to learn about implementing AdaBoost for classifying graduate admission across different programming languages.
diff --git a/...on-classification-with-adaboost-cpp.ipynb → ...on-classification-with-adaboost-cpp.ipynb b/...on-classification-with-adaboost-cpp.ipynb → ...on-classification-with-adaboost-cpp.ipynb
diff --git a/...ion-classification-with-adaboost-py.ipynb → ...ion-classification-with-adaboost-py.ipynb b/...ion-classification-with-adaboost-py.ipynb → ...ion-classification-with-adaboost-py.ipynb
diff --git a/iris-classification/README.md b/iris-classification/README.md
@@ -0,0 +1,11 @@
+# Iris Classification
+
+This directory contains machine learning examples focusing on classifying iris flowers using various classification algorithms in Python.
+
+## Directories
+- `py`: Contains Python implementations.
+
+## Files
+- `py/iris-classification-py.ipynb`: Notebook showcasing iris flower classification using Python.
+
+Explore the notebook to learn about implementing classification algorithms for classifying iris flowers in Python.
diff --git a/...assification/iris-classification-py.ipynb → ...ation/python/iris-classification-py.ipynb b/...assification/iris-classification-py.ipynb → ...ation/python/iris-classification-py.ipynb
diff --git a/loan_default_prediction_with_decision_tree/README.md b/loan_default_prediction_with_decision_tree/README.md
@@ -0,0 +1,13 @@
+# Loan Default Prediction with Decision Tree
+
+This directory contains machine learning examples focusing on predicting loan defaults using decision trees in different programming languages.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `py`: Contains Python implementations.
+
+## Files
+- `cpp/loan-default-prediction-with-decision-tree-cpp.ipynb`: Notebook demonstrating loan default prediction using decision trees in C++.
+- `py/loan-default-prediction-with-decision-tree-py.ipynb`: Notebook showcasing loan default prediction using decision trees in Python.
+
+Explore the notebooks to learn about implementing decision trees for predicting loan defaults across different programming languages.
diff --git a/...t-prediction-with-decision-tree-cpp.ipynb → ...t-prediction-with-decision-tree-cpp.ipynb b/...t-prediction-with-decision-tree-cpp.ipynb → ...t-prediction-with-decision-tree-cpp.ipynb
diff --git a/...lt-prediction-with-decision-tree-py.ipynb → ...lt-prediction-with-decision-tree-py.ipynb b/...lt-prediction-with-decision-tree-py.ipynb → ...lt-prediction-with-decision-tree-py.ipynb
diff --git a/lstm_electricity_consumption/README.md b/lstm_electricity_consumption/README.md
@@ -0,0 +1,13 @@
+# LSTM Electricity Consumption Forecasting
+
+This directory contains machine learning examples focusing on forecasting electricity consumption using LSTM (Long Short-Term Memory) networks.
+
+## Directories
+- `C++`: Contains C++ implementations and Makefiles.
+
+## Files
+- `C++/lstm_electricity_consumption.cpp`: C++ code demonstrating LSTM-based electricity consumption forecasting.
+- `C++/Makefile`: Makefile for compiling the C++ code.
+- `C++/tutorial.txt`: Tutorial file providing additional information and instructions.
+
+Explore the C++ code and tutorial to learn about implementing LSTM networks for electricity consumption forecasting.
diff --git a/lstm_electricity_consumption/Makefile → lstm_electricity_consumption/cpp/Makefile b/lstm_electricity_consumption/Makefile → lstm_electricity_consumption/cpp/Makefile
diff --git a/...sumption/lstm_electricity_consumption.cpp → ...tion/cpp/lstm_electricity_consumption.cpp b/...sumption/lstm_electricity_consumption.cpp → ...tion/cpp/lstm_electricity_consumption.cpp
diff --git a/lstm_electricity_consumption/tutorial.txt → ..._electricity_consumption/cpp/tutorial.txt b/lstm_electricity_consumption/tutorial.txt → ..._electricity_consumption/cpp/tutorial.txt
diff --git a/...multivariate_time_series_prediction.ipynb → ...multivariate_time_series_prediction.ipynb b/...multivariate_time_series_prediction.ipynb → ...multivariate_time_series_prediction.ipynb
diff --git a/lstm_stock_prediction/README.md b/lstm_stock_prediction/README.md
@@ -0,0 +1,20 @@
+# LSTM Electricity Consumption Forecasting
+
+This directory contains machine learning examples focusing on forecasting electricity consumption using LSTM (Long Short-Term Memory) networks.
+
+## Directories
+- `C++`: Contains C++ implementations and Makefiles.
+- `Jupyter_notebook_code`: Contains code relative to Jupyter notebooks.
+
+## Files
+### C++ Examples
+- `C++/lstm_electricity_consumption.cpp`: C++ code demonstrating LSTM-based electricity consumption forecasting.
+- `C++/Makefile`: Makefile for compiling the C++ code.
+
+### Jupyter Notebook Example
+- `Jupyter_notebook_code/lstm_multivariate_time_series_prediction.ipynb`: Notebook illustrating multivariate time series prediction using LSTM.
+
+### Additional Resources
+- `tutorial.txt`: Tutorial file providing additional information and instructions.
+
+Explore the code and tutorial to learn about implementing LSTM networks for electricity consumption forecasting.
diff --git a/lstm_stock_prediction/Makefile → lstm_stock_prediction/cpp/Makefile b/lstm_stock_prediction/Makefile → lstm_stock_prediction/cpp/Makefile
diff --git a/...tock_prediction/lstm_stock_prediction.cpp → ..._prediction/cpp/lstm_stock_prediction.cpp b/...tock_prediction/lstm_stock_prediction.cpp → ..._prediction/cpp/lstm_stock_prediction.cpp
diff --git a/lstm_stock_prediction/tutorial.txt → lstm_stock_prediction/cpp/tutorial.txt b/lstm_stock_prediction/tutorial.txt → lstm_stock_prediction/cpp/tutorial.txt
diff --git a/microchip_quality_control_naive_bayes/README.md b/microchip_quality_control_naive_bayes/README.md
@@ -0,0 +1,16 @@
+# Microchip Quality Control with Naive Bayes
+
+This directory contains machine learning examples focusing on microchip quality control using Naive Bayes classification.
+
+## Directories
+- `C++`: Contains C++ implementations.
+- `Python`: Contains Python implementations.
+
+## Files
+### C++ Example
+- `C++/microchip-quality-control-naive-bayes-cpp.ipynb`: Notebook demonstrating microchip quality control using Naive Bayes in C++.
+
+### Python Example
+- `Python/microchip-quality-control-naive-bayes-py.ipynb`: Notebook showcasing microchip quality control using Naive Bayes in Python.
+
+Explore the notebooks to learn about implementing Naive Bayes classification for microchip quality control in C++ and Python.
diff --git a/...hip-quality-control-naive-bayes-cpp.ipynb → ...hip-quality-control-naive-bayes-cpp.ipynb b/...hip-quality-control-naive-bayes-cpp.ipynb → ...hip-quality-control-naive-bayes-cpp.ipynb
diff --git a/...chip-quality-control-naive-bayes-py.ipynb → ...chip-quality-control-naive-bayes-py.ipynb b/...chip-quality-control-naive-bayes-py.ipynb → ...chip-quality-control-naive-bayes-py.ipynb
diff --git a/mnist_batch_norm/Makefile → mnist_batch_norm/cpp/Makefile b/mnist_batch_norm/Makefile → mnist_batch_norm/cpp/Makefile
diff --git a/mnist_batch_norm/mnist_batch_norm.cpp → mnist_batch_norm/cpp/mnist_batch_norm.cpp b/mnist_batch_norm/mnist_batch_norm.cpp → mnist_batch_norm/cpp/mnist_batch_norm.cpp
diff --git a/mnist_cnn/Makefile → mnist_cnn/cpp/Makefile b/mnist_cnn/Makefile → mnist_cnn/cpp/Makefile
diff --git a/mnist_cnn/mnist_cnn.cpp → mnist_cnn/cpp/mnist_cnn.cpp b/mnist_cnn/mnist_cnn.cpp → mnist_cnn/cpp/mnist_cnn.cpp
diff --git a/mnist_cnn_f32/Makefile → mnist_cnn_f32/cpp/Makefile b/mnist_cnn_f32/Makefile → mnist_cnn_f32/cpp/Makefile
diff --git a/mnist_cnn_f32/mnist_cnn_f32.cpp → mnist_cnn_f32/cpp/mnist_cnn_f32.cpp b/mnist_cnn_f32/mnist_cnn_f32.cpp → mnist_cnn_f32/cpp/mnist_cnn_f32.cpp
diff --git a/mnist_simple/Makefile → mnist_simple/cpp/Makefile b/mnist_simple/Makefile → mnist_simple/cpp/Makefile
diff --git a/mnist_simple/mnist_simple.cpp → mnist_simple/cpp/mnist_simple.cpp b/mnist_simple/mnist_simple.cpp → mnist_simple/cpp/mnist_simple.cpp
diff --git a/mnist_simple_f32/Makefile → mnist_simple_f32/cpp/Makefile b/mnist_simple_f32/Makefile → mnist_simple_f32/cpp/Makefile
diff --git a/mnist_simple_f32/mnist_simple_f32.cpp → mnist_simple_f32/cpp/mnist_simple_f32.cpp b/mnist_simple_f32/mnist_simple_f32.cpp → mnist_simple_f32/cpp/mnist_simple_f32.cpp
diff --git a/mnist_vae_cnn/README.md b/mnist_vae_cnn/README.md
@@ -0,0 +1,21 @@
+# MNIST Variational Autoencoder with CNN
+
+This directory contains machine learning examples focusing on implementing a Variational Autoencoder (VAE) with Convolutional Neural Networks (CNN) for the MNIST dataset.
+
+## Directories
+- `images`: Contains images used in the examples.
+  - `latent`: Contains samples generating code from models repo.
+  - `samples_posterior`: Contains samples generating code from models repo.
+  - `samples_prior`: Contains samples generating code from models repo.
+
+## Files
+### C++ Implementations
+- `C++/Makefile`: Makefile for compiling the C++ code.
+- `C++/mnist_vae_cnn.cpp`: C++ code demonstrating VAE with CNN for MNIST dataset.
+- `C++/vae_generate.cpp`: C++ code for generating VAE samples.
+- `C++/vae_utils.hpp`: Header file containing utility functions.
+
+### Python Implementation
+- `generate_images.py`: Python script for generating samples.
+
+Explore the code, directories, and images to learn about implementing VAE with CNN for the MNIST dataset.
diff --git a/mnist_vae_cnn/Makefile → mnist_vae_cnn/cpp/Makefile b/mnist_vae_cnn/Makefile → mnist_vae_cnn/cpp/Makefile
diff --git a/mnist_vae_cnn/mnist_vae_cnn.cpp → mnist_vae_cnn/cpp/mnist_vae_cnn.cpp b/mnist_vae_cnn/mnist_vae_cnn.cpp → mnist_vae_cnn/cpp/mnist_vae_cnn.cpp
diff --git a/mnist_vae_cnn/vae_generate.cpp → mnist_vae_cnn/cpp/vae_generate.cpp b/mnist_vae_cnn/vae_generate.cpp → mnist_vae_cnn/cpp/vae_generate.cpp
diff --git a/mnist_vae_cnn/vae_utils.hpp → mnist_vae_cnn/cpp/vae_utils.hpp b/mnist_vae_cnn/vae_utils.hpp → mnist_vae_cnn/cpp/vae_utils.hpp
diff --git a/mnist_vae_cnn/latent/allSamples.jpg → ...e_cnn/images/images/latent/allSamples.jpg b/mnist_vae_cnn/latent/allSamples.jpg → ...e_cnn/images/images/latent/allSamples.jpg
diff --git a/..._vae_cnn/samples_posterior/allSamples.jpg → ...s/images/samples_posterior/allSamples.jpg b/..._vae_cnn/samples_posterior/allSamples.jpg → ...s/images/samples_posterior/allSamples.jpg
diff --git a/mnist_vae_cnn/samples_prior/2dLatent.jpg → .../images/images/samples_prior/2dLatent.jpg b/mnist_vae_cnn/samples_prior/2dLatent.jpg → .../images/images/samples_prior/2dLatent.jpg
diff --git a/mnist_vae_cnn/samples_prior/allLatent.jpg → ...images/images/samples_prior/allLatent.jpg b/mnist_vae_cnn/samples_prior/allLatent.jpg → ...images/images/samples_prior/allLatent.jpg
diff --git a/mnist_vae_cnn/samples_prior/allSamples.jpg → ...mages/images/samples_prior/allSamples.jpg b/mnist_vae_cnn/samples_prior/allSamples.jpg → ...mages/images/samples_prior/allSamples.jpg
diff --git a/mnist_vae_cnn/generate_images.py → mnist_vae_cnn/python/generate_images.py b/mnist_vae_cnn/generate_images.py → mnist_vae_cnn/python/generate_images.py
diff --git a/movie_lens_prediction_with_cf/README.md b/movie_lens_prediction_with_cf/README.md
@@ -0,0 +1,16 @@
+# Movie Lens Recommendation with Collaborative Filtering
+
+This directory contains machine learning examples focusing on movie recommendation using Collaborative Filtering.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `Python`: Contains Python implementations.
+
+## Files
+### C++ Example
+- `cpp/movie-lens-cf-cpp.ipynb`: Notebook demonstrating movie recommendation using Collaborative Filtering in C++.
+
+### Python Example
+- `Python/movie-lens-cf-py.ipynb`: Notebook showcasing movie recommendation using Collaborative Filtering in Python.
+
+Explore the notebooks to learn about implementing Collaborative Filtering for movie recommendation in C++ and Python.
diff --git a/...rediction_with_cf/movie-lens-cf-cpp.ipynb → ...ction_with_cf/cpp/movie-lens-cf-cpp.ipynb b/...rediction_with_cf/movie-lens-cf-cpp.ipynb → ...ction_with_cf/cpp/movie-lens-cf-cpp.ipynb
diff --git a/...prediction_with_cf/movie-lens-cf-py.ipynb → ...ion_with_cf/python/movie-lens-cf-py.ipynb b/...prediction_with_cf/movie-lens-cf-py.ipynb → ...ion_with_cf/python/movie-lens-cf-py.ipynb
diff --git a/neural_network_regression/README.md b/neural_network_regression/README.md
@@ -0,0 +1,19 @@
+# Neural Network Regression
+
+This directory contains machine learning examples focusing on regression tasks using Neural Networks.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `jupiter_notebook_code`: Contains Jupyter notebook implementations.
+
+## Files
+### C++ Example
+- `cpp/nn_regression.cpp`: C++ code demonstrating neural network regression.
+
+### Jupyter Notebook
+- `jupiter_notebook_code/neural_network_regression.ipynb`: Notebook illustrating neural network regression.
+
+### Additional Files
+- `Makefile`: Makefile for compiling the C++ code.
+
+Explore the code and notebooks to learn about implementing neural network regression in C++ and Jupyter notebook.
diff --git a/neural_network_regression/Makefile → neural_network_regression/cpp/Makefile b/neural_network_regression/Makefile → neural_network_regression/cpp/Makefile
diff --git a/neural_network_regression/nn_regression.cpp → ..._network_regression/cpp/nn_regression.cpp b/neural_network_regression/nn_regression.cpp → ..._network_regression/cpp/nn_regression.cpp
diff --git a/...egression/neural_network_regression.ipynb → ...book_code/neural_network_regression.ipynb b/...egression/neural_network_regression.ipynb → ...book_code/neural_network_regression.ipynb
diff --git a/pima_indians_diabetes_clustering_with_kmeans/README.md b/pima_indians_diabetes_clustering_with_kmeans/README.md
@@ -0,0 +1,12 @@
+# Pima Indians Diabetes Clustering with K-means
+
+This directory contains machine learning examples focusing on clustering the Pima Indians Diabetes dataset using K-means.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+
+## Files
+### C++ Example
+- `cpp/pima-indians-diabetes-kmeans-cpp.ipynb`: Notebook demonstrating K-means clustering on the Pima Indians Diabetes dataset using C++.
+
+Explore the notebook to learn about implementing K-means clustering for the Pima Indians Diabetes dataset in C++.
diff --git a/...ns/pima-indians-diabetes-kmeans-cpp.ipynb → ...pp/pima-indians-diabetes-kmeans-cpp.ipynb b/...ns/pima-indians-diabetes-kmeans-cpp.ipynb → ...pp/pima-indians-diabetes-kmeans-cpp.ipynb
diff --git a/portfolio_optimization/cpp/README.md b/portfolio_optimization/cpp/README.md
@@ -0,0 +1,12 @@
+# Portfolio Optimization
+
+This directory contains machine learning examples focusing on portfolio optimization.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+
+## Files
+### C++ Example
+- `cpp/portfolio-optimization-cpp.ipynb`: Notebook demonstrating portfolio optimization using C++.
+
+Explore the notebook to learn about implementing portfolio optimization in C++.
diff --git a/...mization/portfolio-optimization-cpp.ipynb → ...tion/cpp/portfolio-optimization-cpp.ipynb b/...mization/portfolio-optimization-cpp.ipynb → ...tion/cpp/portfolio-optimization-cpp.ipynb
diff --git a/rain_in_australia_classification/README.md b/rain_in_australia_classification/README.md
@@ -0,0 +1,12 @@
+# Rain in Australia Classification
+
+This directory contains machine learning examples focusing on predicting rain in Australia using classification methods.
+
+## Directories
+- `Python`: Contains Python implementations.
+
+## Files
+### Python Example
+- `Python/rain_in_australia_classification_py.ipynb`: Notebook demonstrating rain prediction in Australia using classification in Python.
+
+Explore the notebook to learn about implementing classification for rain prediction in Australia using Python.
diff --git a/...rain_in_australia_classification_py.ipynb → ...rain_in_australia_classification_py.ipynb b/...rain_in_australia_classification_py.ipynb → ...rain_in_australia_classification_py.ipynb
diff --git a/rainfall_prediction_with_random_forest/README.md b/rainfall_prediction_with_random_forest/README.md
@@ -0,0 +1,16 @@
+# Rainfall Prediction with Random Forest
+
+This directory contains machine learning examples focusing on predicting rainfall using Random Forest.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `Python`: Contains Python implementations.
+
+## Files
+### C++ Example
+- `cpp/rainfall-prediction-with-random-forest-cpp.ipynb`: Notebook demonstrating rainfall prediction using Random Forest in C++.
+
+### Python Example
+- `Python/rainfall-prediction-with-random-forest-py.ipynb`: Notebook showcasing rainfall prediction using Random Forest in Python.
+
+Explore the notebooks to learn about implementing Random Forest for rainfall prediction in C++ and Python.
diff --git a/...l-prediction-with-random-forest-cpp.ipynb → ...l-prediction-with-random-forest-cpp.ipynb b/...l-prediction-with-random-forest-cpp.ipynb → ...l-prediction-with-random-forest-cpp.ipynb
diff --git a/...ll-prediction-with-random-forest-py.ipynb → ...ll-prediction-with-random-forest-py.ipynb b/...ll-prediction-with-random-forest-py.ipynb → ...ll-prediction-with-random-forest-py.ipynb
diff --git a/rocket_injector_design/README.md b/rocket_injector_design/README.md
@@ -0,0 +1,18 @@
+# Rocket Injector Design
+
+This directory contains machine learning examples focusing on rocket injector design.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+
+## Files
+### C++ Example
+- `cpp/rocket-injector-design-cpp.ipynb`: Notebook demonstrating rocket injector design using C++.
+
+## Media
+- `combustion.gif`: GIF illustrating combustion.
+- `design.jpg`: Image depicting the design process.
+- `objectives.jpg`: Image showing the objectives.
+- `unstable.gif`: GIF showing unstable behavior.
+
+Explore the notebook and media files to learn about implementing rocket injector design in C++.
diff --git a/...r_design/rocket-injector-design-cpp.ipynb → ...sign/cpp/rocket-injector-design-cpp.ipynb b/...r_design/rocket-injector-design-cpp.ipynb → ...sign/cpp/rocket-injector-design-cpp.ipynb
diff --git a/salary_prediction_with_linear_regression/README.md b/salary_prediction_with_linear_regression/README.md
@@ -0,0 +1,16 @@
+# Salary Prediction with Linear Regression
+
+This directory contains machine learning examples focusing on salary prediction using Linear Regression.
+
+## Directories
+- `cpp`: Contains C++ implementations.
+- `Python`: Contains Python implementations.
+
+## Files
+### C++ Example
+- `cpp/salary-prediction-linear-regression-cpp.ipynb`: Notebook demonstrating salary prediction using Linear Regression in C++.
+
+### Python Example
+- `Python/salary-prediction-linear-regression-py.ipynb`: Notebook showcasing salary prediction using Linear Regression in Python.
+
+Explore the notebooks to learn about implementing Linear Regression for salary prediction in C++ and Python.
diff --git a/...ry-prediction-linear-regression-cpp.ipynb → ...ry-prediction-linear-regression-cpp.ipynb b/...ry-prediction-linear-regression-cpp.ipynb → ...ry-prediction-linear-regression-cpp.ipynb
diff --git a/...ary-prediction-linear-regression-py.ipynb → ...ary-prediction-linear-regression-py.ipynb b/...ary-prediction-linear-regression-py.ipynb → ...ary-prediction-linear-regression-py.ipynb