Tutorials and my solutions to the Udacity NLP Nanodegree

Project Portfolio for Machine Learning Nanodegree by Udacity

Projects I implemented to finish Udacity Nanodegree Programs from Data Engineering to Machine Learning Engineering.

Investigated factors affecting likelihood of donations being made using real census data. Developed naive classifier to compare testing results. Trained & tested several supervised machine learning models on preprocessed census data to predict donation likelihood. Selected best model based on accuracy, modified F-score metric, & algo efficiency.

Udacity Deep Learning Nanodegree Project 1 on bike-sharing patterns. Do 🌟 it and show some love

🔫 The data comes from the FBI's National Instant Criminal Background Check System. The NICS is used by to determine whether a prospective buyer is eligible to buy firearms or explosives. 🔫

Overview of the Udacity Data Analyst Nanodegree

Project 4 - Google Udacity India Scholars 2018, Android Developer Nanodegree.

Deep Learning https://dtflaneur.wordpress.com/category/dl/

The dataset that we will be wrangling (and analysing and visualising) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog.

Generate TV Scripts using RNN and LSTM

Udacity's NLPND Hidden Markov Model Part of Speech tagger project

Finding Lane Lines on the Road part of my nanodegree self driving car

Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modelling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.

Movie Trailer Site

In this project, I'll generate Seinfeld TV scripts using RNNs and part of the Seinfeld dataset of scripts from 9 seasons.

This Project analyse the date of TMDb - Movies _ Udacity second Project

Udacity Front-End Web Developer Nanodegree - Project 1: Mockup to Website

Generated faces from a pair of multi-layer neural networks generator and discriminator that compete against each other until one learns to generate realistic images of faces using CelebFaces Attributes (CelebA) dataset.