CAPSTONE PROJECT SWIFTKEY

The app is extremely intuitive. It allows native German-speakers to use the app as well experimental. Your heart will beat more rapidly and you’ll smile for no reason. Data Visualization Now that the data is cleaned, we can visualize our data to better understand what we are working with. Today is a great … day. But typing on mobile devices becomes a serious pain for many cases. Data Processing After we load libraries our first step is to get the data set from the Coursera website.

Once a cleaned set of text source was available in form of n-gram tables, I began to implement and test a variety features. Our second step is to load the date set into R. Now that the data is cleaned, we can visualize our data to better understand what we are working with. We notice three different distinct text files all in English language. Possibly removing the list of English stop words is not necessary for building this SmartKey product, but it is a reasonable starting point to remove and see. We also want to perform some level of profanity filtering to remove profanity and other words that we do not want to predict.

We are given datasets for training purposes, which can be downloaded from this link.

capstone project swiftkey

Btw thanks for the RT. The goal of this capstone project is for the student to learn the basics of Natural Language Processing NLP and to swictkey that the student can explore a new data type, quickly get up to speed on a new application, and implement a useful model in a reasonable period of time.

  UIOWA DISSERTATION EMBARGO

SwiftKey Capstone Project – Milestone Report

From our data processing we noticed the data sets are very big. An excerpt of text cleaning and other transformations: Prjoect and SwiftKey have partnered to create this capstone project as the final project for the Data Scientist Specilization from Coursera. Conversion of text to lower case and removal of any unnecessary whitespaces.

By the usage of the tokenizer function for the n-grams a distribution of the following top 10 words and word combinations can be inspected. The project includes but is not limited too: The ultimate goal for this capstone project is to predict the next word capshone on a secuence of words typed as input.

Data Preparation From our data processing we noticed the data sets are very big.

Speed will be important as we move to the shiny application. Our second step is to load the date set into R. Learned the hard way, but I ended up creating a much smaller sample of the raw data with less information to decrease processing time. In this capstone, we will work on building predictive text models which could present three options for what the next word prpject be when people type on their mobile devices.

capstone project swiftkey

Post A Comment Cancel Reply. Nowadays, people are spending great amount of time on mobile devices. Now that the data is cleaned, we can visualize our data to better understand what we are working with. The projeft is extremely intuitive. Cleaning the data is a critical step for ngram and tokenization process.

capstone project swiftkey

So before proceeding any further, we clean things up a bit. Less data has its cost, I assume it will decrease the accuracy of the prediction.

  DERBORENCE RAMUZ DISSERTATION

Possibly removing the list of English stop words prkject not necessary for building this SmartKey product, but it is a reasonable starting point to remove and see.

RPubs – JHU Swiftkey Capstone Project

We must clean the data set. Been way, way too long. It allows native German-speakers to use the app as well experimental. We also want to perform some level of profanity filtering to remove profanity and other words that we do not want to predict.

Removal of any Internet related content hyperlinks, emails, retweets. The prediction model is based on three different sources of text blogs, news, tweets.

SwiftKey Capstone Project – Milestone Report

But typing on mobile devices becomes a serious pain for many cases. As a next step, I created 4 n-gram tables: Once a cleaned set of text source was available in form of n-gram tables, I began to implement and test a variety features.

Your heart will beat more rapidly and you’ll smile for no reason. The objective of the capstone project was to 1 build a swiftoey that predicts the next term in a sequence swictkey words, and to 2 encapsulate the result in an appropriate user interface using Shiny.

You gonna be in DC anytime soon?