Tutorials and my solutions to the Udacity NLP Nanodegree
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Updated
Sep 13, 2018 - HTML
Tutorials and my solutions to the Udacity NLP Nanodegree
Projects created from Udacity's Data Analyst Nanodegree
Project work for the Udacity Data Analyst Nanodegree
Projects I implemented to finish Udacity Nanodegree Programs from Data Engineering to Machine Learning Engineering.
These are the projects I did on my Udacity Deep Learning Nanodegree 🌟 💻 💻. 💥 🌈
Finding Donors for Charity - 3rd project for Udacity's Machine Learning Nanodegree
Dog Breed classifier project of the Data Scientist Nanodegree by Udacity. A Web Application is developed using Flask through which a user can check if an uploaded image is that of a dog or human. Also, if the uploaded image is that of a human, the algorithm tells the user what dog breed the human resembles the most. The Deep Learning model disti…
Udacity Nanodegree - Data Analyst - Wrangling, Exploring, Analyzing, and Visualizing Data
AIML Programming with PyTorch
Deep Learning Udacity Nanodegree - SageMaker Deployment of a Sentiment Analysis model
All the projects I completed while doing Robotics Nanodegree
Investigating Movies Dataset contains information about 10,000+ movies collected from The Movie Database (TMDb)
Udacity Nanodegree Deep Learning Foundations
Experimental Design & Recommendations Project of Udacity Data Scientist Nanodegree
This project is a part of the Data Scientist Nanodegree by Udacity. It features an important collaboration with IBM, the provider of the dataset. The aim is to develop a recommendation engine and suggest new articles to the IBM Watson Community users.
Udacity Deep Learning Nanodegree Project 1 on bike-sharing patterns. Do 🌟 it and show some love
Udacity - Data Analyst Nanodegree - Project 5 - Data Visualization
Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree
Second project of the Udacity Machine Learning Engineer Nanodegree program where a Plagiarism Detector is created using custom similarity features amongst source and answer file such as containment and longest common subsequence. Further, trained and deployed the model on Amazon Sagemaker.
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