Lending Club Data Analysis
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Updated
Apr 29, 2019 - Jupyter Notebook
Lending Club Data Analysis
A compilation of Machine Learning Notebooks for beginners.
Report on the AutoKeras Network Architecture Search.
Bike sharing systems are a means of renting bicycles where the process of obtaining membership, rental, and bike return is automated via a network of kiosk locations throughout a city. Using these systems, people are able rent a bike from a one location and return it to a different place on an as-needed basis. Currently, there are over 500 bike-…
This repository contains my starter-kit for learning Data Science from scratch. The aim is to work in tiny increments, learning one or two new things with each project, as well as finding one thing that can be improved with each project. The philosophy is quantity over quality for foundational learning.
CS791: High Performance Computing and Networking, Spring 2022, E. Arslan
Bike sharing demand prediction using Autogluon ML.
This repository showcases a Convolutional Neural Network (CNN) module developed on Jupyter and an AutoML module implemented on Google Cloud Platform (GCP) through VertexAI
It's all about Data's importance in shaping our modern world and driving insightful decisions.
The "Chicago Taxi Fare Prediction" project aims to develop a machine learning model using Vertex AI AutoML that can be used for taxi fare prediction in the Chicago area. The location was obtained using the Google Places API, while the distance and duration were obtained using the Google Distance Matrix API.
Honing Professional ML skills by solving Kaggle Competitions using ML tools from Google Cloud and ML Best Practices. Analyzing the Winner Solutions.
This web application is motivated by Baymax of the animated movie Big Hero 6. It detects Valvular Heart disorder i.e. damage or defect in one of the four heart valves. On the Machine Learning side, I have used AutoML from the deep learning platform H2O. And the interactive application is build in RShiny.
Azure ML Pipeline Project, completed for Nanodegree
Project from my Machine Learning Engineer with Azure Nano-Degree program at Udacity
This is first of the three projects required for fulfillment of the Nanodegree Machine Learning Engineer with Microsoft Azure from Udacity. In this project, we build and optimize an Azure ML pipeline using the Python SDK and a provided Scikit-learn model. This model is then compared to an Azure AutoML run.
A low code, low-cost AutoML solution for tabular data.
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