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    <title>Data Science Portfolio on Peter Le</title>
    <link>https://peterle93.github.io/Peter_Portfolio/</link>
    <description>Recent content in Data Science Portfolio on Peter Le</description>
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      <title>Customer Churn Prediction with Spark</title>
      <link>https://peterle93.github.io/Peter_Portfolio/post/project-5/</link>
      <pubDate>Mon, 01 Feb 2021 10:58:08 -0400</pubDate>
      
      <guid>https://peterle93.github.io/Peter_Portfolio/post/project-5/</guid>
      <description>Overview
Customer churn prevention is a hot and challenging problem in almost every product and service company. If companies were able to utilize customer-usage data to find unique trends and accurately map them to indicate which customers may churn, it’s possible to incentivize customers to remain using their services giving them a loyal customer base which is key for a company’s growth.
Sparkify is a digital music service similar to Spotify and Pandora.</description>
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      <title>Recommendations with IBM</title>
      <link>https://peterle93.github.io/Peter_Portfolio/post/project-4/</link>
      <pubDate>Wed, 20 Jan 2021 11:14:48 -0400</pubDate>
      
      <guid>https://peterle93.github.io/Peter_Portfolio/post/project-4/</guid>
      <description>For this project, we will analyze the interactions users have with articles on the IBM Watson Studio platorm and provide recommendations on which new articles you think they will like. To determine which articles to show to each user, we will be performing a study of the data available on the IBM Watson Studio platform.
The project will be divided into the following parts:
I. Exploratory Data Analysis Before making recommendations, we will did to explore the data that we are working with for the project.</description>
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      <title>Disaster Response Pipeline</title>
      <link>https://peterle93.github.io/Peter_Portfolio/post/project-3/</link>
      <pubDate>Thu, 17 Dec 2020 11:13:32 -0400</pubDate>
      
      <guid>https://peterle93.github.io/Peter_Portfolio/post/project-3/</guid>
      <description>Disaster Response Pipeline Project The goal of the project is to classify legitimate messages sent during disaster events from a dataset provided by Figure Eight. It requires us to build machine learning pipeline to categorize emergency messages according to the needs communicated by the sender on a real time basis. The specific machine model is a Natural Language Processing (NLP) model.
The project is divided into three main sections:
Building an ETL pipeline to extract data, cleaning the data and storing it into a SQlite Database.</description>
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      <title>Things to know before planning a trip to Toronto</title>
      <link>https://peterle93.github.io/Peter_Portfolio/post/project-2/</link>
      <pubDate>Wed, 02 Dec 2020 11:00:59 -0400</pubDate>
      
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      <description>Toronto Airbnb Dataset Analysis
The Motivation for the Project
This project (Write a Data Science Blog Post) is part of Udacity Data Scientist Nanodegree Program. I used Toronto Airbnb Dataset for this project as its the city I live in. I&amp;rsquo;m interested in using data science techniques to analyze ways to improve future listings. The questions analyzed may be similar to data sources one might encounter in a business setting. Additionally, many of the approaches and skills used in this project can be applicable to future work projects.</description>
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      <title>Battle of Neighborhoods</title>
      <link>https://peterle93.github.io/Peter_Portfolio/post/project-1/</link>
      <pubDate>Sat, 28 Nov 2020 10:58:08 -0400</pubDate>
      
      <guid>https://peterle93.github.io/Peter_Portfolio/post/project-1/</guid>
      <description>Overview
The purpose of this project is to assist people in researching the most optimal and resourceful locations near their neighborhood. It will provide the necessary information in making the best decision on selecting the neighborhood you would like to live in.
Many people move into parts of Canada and need tons of prior research dealing with factors such as suitable housing prices, well-known schools for their children, and so on.</description>
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      <title>Contact</title>
      <link>https://peterle93.github.io/Peter_Portfolio/contact/</link>
      <pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate>
      
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      <description>   Follow me on these social media platforms.      Platform URL   Email: le.peter1993@gmail.com   Website: https://peterle93.github.io/Peter_Portfolio/   Twitter: https://twitter.com/lepeter93   LinkedIn: www.linkedin.com/in/peter-le-63b166121   Medium: https://le-peter1993.medium.com/   GitHub: https://github.com/peterle93    </description>
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