Pinned Repositories
aaltd18
Data augmentation using synthetic data for time series classification with deep residual networks
ADACS_ML_A
Introduction to time series classification using Keras
albumentations
fast image augmentation library and easy to use wrapper around other libraries
Algorithms
Causal_Inference
Data_analysis_IVF
machine-learning-with-python-cookbook-notes
My jupyter notebooks/code samples from Chris Albon's Machine Learning with Python Cookbook
Python-snipets
R-Tutorials
Statistics-Python-Tutorials
kinokoberuji's Repositories
kinokoberuji/Statistics-Python-Tutorials
kinokoberuji/Python-snipets
kinokoberuji/R-Tutorials
kinokoberuji/Data_analysis_IVF
kinokoberuji/Causal_Inference
kinokoberuji/Algorithms
kinokoberuji/Applied-Longitudinal-Data-Analysis-with-brms-and-the-tidyverse
Translating ML into Bayes, one line at a time
kinokoberuji/attention_keras
Keras Layer implementation of Attention
kinokoberuji/biobankAccelerometerAnalysis
Extracting meaningful health information from large accelerometer datasets
kinokoberuji/Biosignal-analysis
This repo is for tutorials of biosignal analysis
kinokoberuji/data-visualisation-scripts
Collection of scripts for data visualisation and good code practice.
kinokoberuji/deeplearning-tf2
Deep learning model zoo with TensorFlow 2.X (& Keras)
kinokoberuji/dlwpt-code
Code for the book Deep Learning with PyTorch by Eli Stevens and Luca Antiga.
kinokoberuji/Doing-Bayesian-Data-Analysis-in-brms-and-the-tidyverse
The bookdown version lives here: https://bookdown.org/content/3686
kinokoberuji/graph-theory
Python graph traversal algorithm implementation including BFS, DFS, Topological Sort, Dijkstra, Prim, Borůvka, Kruskal, A*, Bellman Ford, Bron Kerbosch
kinokoberuji/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
kinokoberuji/IntroductionAlgorithmsDataStructures
This repository contains the code associated with the "Introduction to Algorithms and Data Structures" Safari Video. https://www.oreilly.com/live-training/courses/introduction-to-algorithms-and-data-structures/0636920306535/
kinokoberuji/kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
kinokoberuji/learn-bayes
learn bayesian with me
kinokoberuji/machine_learning_POC
The repository for various machine learning POC
kinokoberuji/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
kinokoberuji/ml-from-scratch
All the ML algorithms, ML models are coded from scratch by pure Python/Numpy with the Math under the hood. It works well on CPU.
kinokoberuji/OGStats
kinokoberuji/probflow
A Python package for building Bayesian models with TensorFlow or PyTorch
kinokoberuji/pygraphs
Graphs clustering using kernel measures and estimators. Kernel KMeans, Spectral Clustering, Kernel Ward etc.
kinokoberuji/python-runstats
Python module for computing statistics and regression in a single pass.
kinokoberuji/REM-project
kinokoberuji/rethinking-numpyro
Statistical Rethinking (2nd ed.) with NumPyro
kinokoberuji/rethinking-pyro
Statistical Rethinking with PyTorch and Pyro
kinokoberuji/statistical-thinking-data-science
Meus estudos e experimentos para ajudar a consolidar os aprendizados relacionados aos fundamentos de estatística