maryam-ah Goto Github PK
Name: Maryam Ahmadi
Type: User
Bio: Data Scientist
Location: Toronto, Canada
Name: Maryam Ahmadi
Type: User
Bio: Data Scientist
Location: Toronto, Canada
The scope of our analysis will be focused on understanding the environmental variables and determining whether there are key environmental features that lead to a higher number of Dengue fever cases. Our problem statement is: “What environmental features contribute to a higher number of Dengue Fever cases in San Juan and Iquitos
Predicts the occupancy rate defined as a ratio of number of tickets sold to the number of available seats at each location.
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.
Detecting Emotions in children drawings using a Convolutional Neural Network
Encoding categorical variables into numeric variables is part of a data scientist’s daily work. I have been wanting to write down some common Categorical variable encoders.
Housing price competition aims at predicting sale prices for the houses in ‘Ames city’ in Story County, Iowa, United States. The dataset is divided into two halves: testing and training (~50-50%). There are 80 variables in the training dataset.
In this prediction I used Pycaret library to do the prediction and ,y final best model is Bayesian Ridge in compare to Random forest regressor
Pigeon is a simple widget that lets you quickly annotate a dataset of unlabeled examples from the comfort of your Jupyter notebook. Pigeon currently supports annotation for classification tasks (set of labels), regression tasks (int/float range), or captioning tasks (variable-length text). Anything that can be displayed on Jupyter (text, images, audio, graphs, etc.) can be displayed by pigeon by providing the appropriate display_fn argument.
Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft
Offer a new method for Drug - Target Prediction with Drug Repositioning Approach- Introduced a new recommendation system which yielded Machine Learning and Graph Theory methods
Example Azure Pipeline to train and deploy a machine learning model using the Azure Machine Learning service
Predicting the number of empty rooms in each shelter at the city of Toronto with regression model.
Model used: Random Forest classification, AdaBoost classification,Logistic regression with SGD training and KNN classsification. Balance data set methods: Random Under sampling and Random Over Sampling. Evaluation methods: AURUC score, F1 score, Confusion Matrix, Precision score and Recall score
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.