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A cutting edge Open Source HealthCare app(Android+Web) which utilizes Machine Learning to predict diseases based on Symptoms or Natural Language. Also includes features such as Live Chat with Doctors,Appointment Booking,Possible Drugs you can take and Specialist you can refer to.
Singular Spectrum Analysis for time series forecasting in Python
A scikit-learn-compatible module for comparing imputation methods.
Package for reconciliation of hierarchical time series - de Forceville Adrien
Référentiel d'évaluation data science responsable et de confiance
Housing a tutorial for Bayesian Optimization using scikit-optimize Gaussian processes, gradient boosting.
Learning to work with Spark
VIP cheatsheets for Stanford's CS 229 Machine Learning
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.
In this section, I begin with the excel file of sales data, which I obtained from the Tableau Community Forum. As a recall, the data contains mostly categorical variables and components of the vectors from the description column. The index column is a timeseries format. The major objective of this section is to understand the general trends in the data, and gain some quick insights, and then predict and forcast the Sales of the category "Technology" of the given sales data.The statistical significance of these observations will be also tested in 'Exploratory Data Analysis'.
Meetup n°13 Time Series France
This repo is for the Linkedin Learning course: Transformers: Text Classification for NLP using BERT
Create a dataset for teaching machine learning and deep learning
Watson Machine Learning Sample Models
A lead scoring project for the Yotta academy MLE bootcamp
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.