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30-seconds-of-python

A curated collection of useful Python snippets that you can understand in 30 seconds or less.

autonomus-robots-gaming-gui-simulator-in-c

Robotics: Programmed in C a GUI autonomous interaction of two identical robot players called Roger playing ping pong, where Roger detects, chases, and punches the ball to win points when the ball hits the back end of the opposing Roger's field.

cookbook

The Data Engineering Cookbook

creating-customer-segments

An unsupervised learning is used to classify various customers based on annual spending amounts (reported in monetary units) of diverse product categories. One goal of this project is to best describe the variation in the different types of customers that a wholesale distributor interacts with.

data-science-mindset

Resources for Data Science and ML

datasciencecoursera

Data Sharing for Coursera

dbt

dbt

feature-engineering

Tips for Advanced Feature Engineering

feature_selection

finding-donors

The goal with this implementation is to construct a model that accurately predicts whether an individual makes more than $50,000. Several supervised algorithms are employed to accurately model individuals' income using data collected from the 1994 U.S. Census.

gt-nlp-class

Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

hana

hello

image-identification-app

The model is trained using CNN. It accept any user-supplied image as input. If a dog is detected in the image, it will provide an estimate of the dog's breed. If a human is detected, it will provide an estimate of the dog breed that is most resembling.

js

machine-learning

Content for Udacity's Machine Learning curriculum

machine-learning-

Machine Learning Nano Degree

nlp

Natural Language Processing Best Practices & Examples

operationalizing-machine-learning-azure-ml

A classification algorithm is used to train model using AUTO ML and the best model that provides better accuracy is selected and deployed in Azure container instance(ACI). The deployed model provides end point to send request to REST API and also Swagger URI. Document is generated using swagger and models are consumed using end point.

optimizing-an-ml-pipeline-in-azure

build and optimize an Azure ML pipeline using the Python SDK and a provided Scikit-learn model. This model is then compared to a model from Azure AutoML

predicting-time-to-close-incident-azure-ml-capstone

ITSM Incident data from a Service now instance is used predict the time taken for incident to close or resolve it, so that the requester will be informed about ETA ( expected time of accomplishment) Also the prediction for time to close incident helps to analyze if the incident wil miss SLA

python-machine-learning-book

The "Python Machine Learning (1st edition)" book code repository and info resource

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

search-conversion

SAP Conversational AI Skill to access the SAP Help Portal Search API

snowbridge

snowpark-template

Template for snowapark projects

streamlit-example

Example Streamlit app that you can fork to test out share.streamlit.io

train-a-smartcab-to-drive

This is developed based on based on Reinforcement learning. Developed an optimized Q-Learning driving agent that will navigate a Smartcab through its environment towards a goal. Since the Smartcab is expected to drive passengers from one location to another, the driving agent will be evaluated on two very important metrics: Safety and Reliability.

venu212.delegate-incidents-automatically-ml-capstone-

This project helps in identifying an incident and delegate to a specialist, who is responsible for seeing it through to resolution. NLTK and NLP used to parse text data . This helps to manage the day-to-day workflow of your Ops teams by assigning incidents to team members automatically.

venu212.github.io