Pinned Repositories
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
autocorrect
Spelling corrector in python
AutoSeries
Public solution for AutoSeries competition
AutoSeries-1
AutoSeries2019
awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Colibri-digital-test
help_teap
Help Platforma Teap
rev_app
PetricaR's Repositories
PetricaR/awesome-mlops
:sunglasses: A curated list of awesome MLOps tools
PetricaR/awesome-production-machine-learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
PetricaR/help_teap
Help Platforma Teap
PetricaR/rev_app
PetricaR/amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
PetricaR/autocorrect
Spelling corrector in python
PetricaR/AutoSeries
Public solution for AutoSeries competition
PetricaR/AutoSeries-1
PetricaR/AutoSeries2019
PetricaR/Colibri-digital-test
PetricaR/darts
A python library for easy manipulation and forecasting of time series.
PetricaR/Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
PetricaR/ElectricDemandForecasting-DL
Electricity demand forecasting with temporal convolutional networks
PetricaR/EnergyDemandForecastWorkbench
PetricaR/engineering-python
PetricaR/forecasting
Time Series Forecasting Best Practices & Examples
PetricaR/forecastML
An R package with Python support for multi-step-ahead forecasting with machine learning and deep learning algorithms
PetricaR/great_expectations
Always know what to expect from your data.
PetricaR/jupyterlab-dash
An Extension for the Interactive development of Dash apps in JupyterLab
PetricaR/orange3-addons
A list of add-ons for Orange3 add-on dialog
PetricaR/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
PetricaR/Python
:snake: Python Programs
PetricaR/python-holidays
Generate and work with holidays in Python
PetricaR/pyvideo
A Python media index
PetricaR/sktime
A unified toolbox for machine learning with time series
PetricaR/Stock-Prediction-Models
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
PetricaR/test2
PetricaR/time_series
Data package: time series of load, wind and solar generation
PetricaR/TimeSeriesAnalysis
Files for part 1 of my time series analysis video
PetricaR/workstreams
This repository publishes notebooks created as part of an analysis of the 2020 COVID-19 crisis onto the economy, performed by a team of data scientists from IBM and Rolls-Royce for Emergent Alliance.