joseortegalabra Goto Github PK
Name: José Ignacio Ortega Labra
Type: User
Bio: Data Scientist, Ingeniero Civil Industrial, UdeC.
José Ignacio Ortega Labra's Projects
appweb-dashboards-for-ml-projects
Develop app webs - dashboards for show results of machine learning projects
automatic-exploratory-data-analysis
Automatic EDA Write a configuration yml file and run a python script to generate automatic EDA for forecast time series
curso-vscode
El repositorio del curso donde trabajaremos para mejorar el uso de VSCode
data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
ensembles-stackings-methods-regressor
Pruebas diferentes modelos de ensemble [sklearn]
examples-gurobi-ml
Examples using gurobi with machine learning to solve optimizacion problems
explanaible-ai
repo to codes to Explanaible AI
exploratory-data-analysis
notebooks for transversal exploratory data anlysis that can be repeated in almost all datasets
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
identify-data-drift
Repo with differents techniques to identify Data Dritfts
intro-machine-learning
Pruebas y material de estudio del electivo Introduction to Machine Learning / Introducción a la Ciencia de Datos
machine-learning-models
Repo that contain differents codes to train differents ml models
mlbi
Repositorio Ramo Machine Learning for Business Inteligence - Udec 2020-1 (Deep Learning with tensorflow)
offline-evaluation-ml-regression
Offline Evaluation for ML Regression Models
optimization-industrial-process
Repo to show and example of end-to-end industrial project
proyect-gans
Uso de conditional GAN (cGAN) para colorear a color imágenes en blanco y negro. Prueba de la capacidad de la de la red para colorear y dibujar imágenes
pyconcorde
Python wrapper around the Concorde TSP solver
pythondatasciencehandbook
Python Data Science Handbook: full text in Jupyter Notebooks
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
tensorflow
Curso de TensorFlow con Python
tracking-training-ml-models
Explore choices of registry trainings of ml models - mlflow - vertex ai
understanding-consumer-behavior-through-discrete-choise-models
Uso de diferentes tipos de regresiones logísticas para analizar comportamiento del consumidor. Electivo UdeC
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