maryam-ah Goto Github PK

analyzing-dengue-fever-cases-in-san-juan-and-iquitos-with-python

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

attendance-forecasting--predicts-the-occupancy-rate-at-each-cinema-location

Predicts the occupancy rate defined as a ratio of number of tickets sold to the number of available seats at each location.

aws-sagemaker-project

azurepipelineforpredictioncinemaoccupancyrate

brainstation

chd

ci-cd-azure-pipline

deep-learning-containers

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

Detecting Emotions in children drawings using a Convolutional Neural Network

encode-categorical-variables-to-numeric

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.

house-prices-advanced-nn

house-prices-advanced-regression-techniques

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.

house-prices-with-pycaret-library-and-randomforesrreg-and-bayesian-ridge---regression-model

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

insurance-charges-prediction-app-with-azure-and-streamit

iris-classification-azure-streamlit-app

label-data-in-jupyter

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.

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft

mlopddevops

mlops

mlops_complementary

my-resume

network-based-drug-repositioning-using-eigenvector-centrality-measure

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

pipelines-azureml

Example Azure Pipeline to train and deploy a machine learning model using the Azure Machine Learning service

predicting-empty-shelter-for-the-city-of-toronto---regression-model

Predicting the number of empty rooms in each shelter at the city of Toronto with regression model.

predicting-loan-repayment--calssification-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

pycaret-deployment-heroku

real-time-lane-detection-using-opencv

smartcity-with-pycaret

streamlit_app

tableqa-maryam