Turn-in project for Udacity's self-driving car program regarding PID control of a simulated car

Hyper-parameter + encoding + architecture grid/random search for keras

Support Vector machine In detail: /implementation in Python&R/and tuning SVM parameters

Dataset preprocessed, tuned and trained using Support Vector Machine

HYPO_RFS is an algorithm for performing exhaustive grid-search approach for tuning the hyper-parameters of Ranking Feature Selection (RFS) approaches.

The distributed statistical machine translation infrastructure consisting of load balancing, text pre/post-processing and translation services. Written in C++ 11 and utilises multicore CPUs by employing multi-threading, allows for secure SSL/TLS communications.

⚛️ Deep Learning Specialization by deeplearning.ai

Diferentes processos que podem ser usados para encontrar os hyperparâmetros ótimos em aplicações de Inteligência Artificial.

In this repository, a regression analysis is conducted using different machine learning and deep learning models. The study is led in order to choose the most suitable model by looking at different characteristics (models tuning, features scaling, etc).

XTune: A custom python wrapper for XGBoost and LightGBM with numerous utility functions to prevent silly gotchas and save time!

Fractional order proportional derivative controller tuner

Implementation of Deep-learning techniques in pytorch

Breast Cancer Prediction

Manage nginx configuration and vhosts, with letsencrypt support and system tuning

Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause

Deep Learning Nanodegree Project : To generate Simpsons TV scripts using part of the Simpsons data-set of scripts from 27 seasons.

Swarming behaviour is based on aggregation of simple drones exhibiting basic instinctive reactions to stimuli. However, to achieve overall balanced/interesting behaviour the relative importance of these instincts, as well their internal parameters, must be tuned. In this project, you will learn how to apply Genetic Programming as means of such t…

R package to tune parameters for machine learning(Support Vector Machine, Random Forest, and Xgboost), using bayesian optimization with gaussian process