HenrryVargas
Ingeniero en sistemas, machine learning engineer nanodegree, MBA, Business IT certficated
@Nut-IA España
Pinned Repositories
data-science-stack-cookiecutter
Cookiecutter to launch an awesome dockerized Data Science toolstack 🐳📊🤓
deep_learning_for_nlp
deep_learning_for_nlp
docker-cookiecutter-data-science
A fork of the cookiecutter-data-science leveraging Docker for local development.
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.
mlops
Machine learning devops
pycaret
An open source, low-code machine learning library in Python
statistical_methods_for_machine_learning
HenrryVargas's Repositories
HenrryVargas/mlops2020
HenrryVargas/examsazure200201
HenrryVargas/awesome-graph
A curated list of resources for graph databases and graph computing tools
HenrryVargas/AI
Microsoft AI
HenrryVargas/keras_tunner_example
HenrryVargas/vpn
HenrryVargas/pandas-profiling
Create HTML profiling reports from pandas DataFrame objects
HenrryVargas/telepresence
Local development against a remote Kubernetes or OpenShift cluster
HenrryVargas/Python
All Algorithms implemented in Python
HenrryVargas/mlcourse.ai
Open Machine Learning Course
HenrryVargas/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.
HenrryVargas/ngx-admin
Customizable admin dashboard template based on Angular 8+
HenrryVargas/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
HenrryVargas/DP-200-Implementing-an-Azure-Data-Solution
HenrryVargas/DP-201-Designing-an-Azure-Data-Solution
HenrryVargas/DGraphSample
Analyzing Flight Data with Dgraph and .NET
HenrryVargas/betterlifepsi
Betterlife Intelligent PSI(Purchase, Sales and Inventory) system
HenrryVargas/Production-Level-Deep-Learning
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
HenrryVargas/analytics_vidhya
Codes related to activities on AV including articles, hackathons and discussions.
HenrryVargas/stocking-inventory
Proactively Stocking Inventory using Machine Learning
HenrryVargas/skits
scikit-learn-inspired time series
HenrryVargas/trow
Image Management for Kubernetes Clusters
HenrryVargas/nonconformist
Python implementation of the conformal prediction framework.
HenrryVargas/chart-hyperopt
Helm Chart to deploy hyperopt: Distributed Asynchronous Hyperparameter Optimization in Python
HenrryVargas/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
HenrryVargas/titanic-tf.keras
Train tf.keras model using feature coulmns
HenrryVargas/categorical-encoding
A library of sklearn compatible categorical variable encoders
HenrryVargas/materials
Bonus materials, exercises, and example projects for our Python tutorials
HenrryVargas/pangeo
Pangeo website + discussion of general issues related to the project.
HenrryVargas/dask-kubernetes
Native Kubernetes integration for dask