Machine Learning projects for real case scenarios Support libraries and tools: Numpy, TensorFlow, Keras, Pandas, Matplotlib
| Project Directory | Summary |
|---|---|
| math/0x00-linear_algebra | Linear Algebra scripts in python |
| math/0x01-plotting | Plotting graphics with Matplot lib |
| math/0x02-calculus | Python calculus scripts |
| math/0x03-probability | Python probability and statistics scripts |
| math/0x04-convolutions_and_pooling | Python scripts of conolutions and pooling operations |
| supervised_learning/0x00-binary_classification | Binary calssification scripts of Neural Networks and DNN using OOP |
| supervised_learning/0x01-multiclass_classification | Multiclass calssification of NN using OOP paradigm |
| supervised_learning/0x02-tensorflow | Tensor Flow scripts for binary and multiclass DNN models |
| supervised_learning/0x03-optimization | Optimization algorithms made in python for DNN |
| supervised_learning/0x04-error_analysis | Error analysis scripts for monitoring error in DNN models |
| supervised_learning/0x05-regularization | Python scripts for regularization ML DNN models to avoid overfitting |
| supervised_learning/0x06-keras | Keras scripts for implement DNN models |
| supervised_learning/0x07-cnn | Tensor Flow, Keras and Python scripts for create CNN models |
| supervised_learning/0x08-deep_cnns | Building 5 of the most disruptives Deep neural network architectures |
| supervised_learning/0x09-transfer_learning | Transfer learning application using densenet-121 in CIFAR-10 with keras (other architectures in aux dir) |
| supervised_learning/0x10-nlp_metrics | Implementation of evaluation and monitoring metrics for NLP applications |
| supervised_learning/0x11-attention | Attention mechanisms scripts for NLP nd RNN applications |
| supervised_learning/0x12-transformer_apps | Transformer applications using TensorFlow v2 |
| supervised_learning/0x0A-object_detection | Object detection application using YOLOv3 algorithm from scratch |
| supervised_learning/0x0B-face_verification | Facial recognition application using dlib and open-cv Python |
| supervised_learning/0x0D-RNNs | Recurrent neural networks implementation applying GRU, LSTM and BRNN architectures |
| supervised_learning/0x0E-time_series | Application to forecast and create a prediction for the price of a currency exchange in a certain period of time |
| supervised_learning/0x0F-word_embeddings | Second part of NLP project where some scripts using Word2vec and Glove are used for an NLP application |
| unsupervised_learning/0x00-dimensionality_reduction | Single value decomposition, t-SNE and dimensionality reduction algotrithms implementation |
| unsupervised_learning/0x01-clustering | Several implementation of clustering algorithms from scratch such as k-means, EM, GMM, and Hierarchical clustering |
| unsupervised_learning/0x02-hmm | Hidden Markov Models implementation with python |
| unsupervised_learning/0x03-hyperparameter_tuning | Application that creates custom and efficient hyperparameter tuning for any neural networks using GPy and GPyOpt |
| unsupervised_learning/0x04-autoencoders | Autoencoding implementation for GAN's or dimensionality reduction |
| reinforcement_learning/0x00-q_learning | Skimming reinforment learning concepts by creating a simple game agent |
| reinforcement_learning/0x01-deep_q_learning | Part two of reinforcemnt learning this time leading the game agent implementation with keras RL for an Atari game space invaders |
| pipeline/0x00-pandas | Pandas sripts for preprocessing ML models |
| pipeline/0x01-apis | Scripts for HTTP requests using github API, SpaceX API (unofficial), StarWars API |
This repository used the following main stack:
| Tool/Library |
|---|
| Python |
| Emacs |
| Git |
| Github |
| Bash |
| Vagrant |
| Numpy |
| Matplotlib |
| Tensorflow |
| Keras |
| Pandas |
| Scikit-learn |
| Pycharm Pro |
| Jupyter |
| VS Code |
| nimblebox |
| GoogleColab |