Pinned Repositories
cnn-bayesian-optimization
Implemementação de uma otimização bayesiana aplicada a uma rede neural convolucional.
covid19-chest-x-ray-detection
Detecção de COVID-19 a partir de imagens de raios X de tórax utilizando uma Deep Convolutional Neural Network otimizada.
Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
grid-search-experiment
In this experiment we'll use Grid Search to find better parameters for this model, to reduce the overfitting.
nyc-airbnb-data-analysis
Um projeto “end-to-end” de Machine Learning em dados do Airbnb.
optimization-problems
pairs-trading-strategy
How to build a simple pairs trading strategy in Python.
quant-experiments
Quantitative Research Experiments
sw-effort-predictive-analysis
In this project, Basic Machine Learning concepts were built on Desharnais dataset to built a software effort estimation model using a linear regression model. This statistical model was developed using a non-parametric linear regression algorithm based on the K-Nearest Neighbours (KNN).
toniesteves's Repositories
toniesteves/design-pattern-command
Experimental implementation of design pattern Command in Java
toniesteves/customer-segmentation
Using unsupervised learning methods to help business better understand customers
toniesteves/flask-boilerplate
:rocket: Fully fledged Flask boilerplate code
toniesteves/free-programming-books
:books: Freely available programming books
toniesteves/galactic-conversor
toniesteves/hackerrank
HackerRank solutions
toniesteves/hands-on-machine-learning
Machine learning practice based on the book Hands On Machine Learning with Scikit-Learn & Tensorflow by Aurelien Geron.
toniesteves/java-codes
Java Code Solution of some Interesting problems.
toniesteves/MachineLearning
Udacity course on Machine Learning
toniesteves/restapidemo
toniesteves/SPOT
SPOT algorithm implementation (with variants)
toniesteves/udacity-course
Udacity courses
toniesteves/udemy-dl
Python script to download a udemy.com course, for personal offline use.