Venu Malireddy's repositories
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
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.
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.
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
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.
Data-Science-Mindset
Resources for Data Science and ML
datasciencecoursera
Data Sharing for Coursera
dbt
dbt
feature-engineering
Tips for Advanced Feature Engineering
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"
machine-learning
Content for Udacity's Machine Learning curriculum
Machine-Learning-
Machine Learning Nano Degree
nlp
Natural Language Processing Best Practices & Examples
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
Snowpark-Template
Template for snowapark projects
streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io