My Projects
Citi - Security Analytics
Spring 2017 Internship with IT at Chick-fil-A
Relevant Technologies
(most to least experienced, rated 1 to 10)
Languages
Python(10), JavaScript(7), Java(7), SQL(6), HTML(6), CSS(6), C(2)
Advanced Analytics
PySpark(9), Scikitlearn(8), SplunkML(8), Hadoop(5)
Natural Language Processing
Alexa SDK (9), Fuzzy Levenshtein(9), NLTK (7), Lex(4), Polly(3)
Web Development
NodeJS (7), JQuery(7), Flask (6), Express(6), Bootstrap(5), Angular(2)
Cloud Computing
Lambda(8), S3(8), Elastic Beanstalk(7), Elastic Map Reduce(7), Docker(4)
Data Visualization
Plotly(10), Matplotlib(9), Tableau(4), D3(4)
Database
DynamoDB(8), PostgreSQL(5), SQLAlchemy(4)
Interactive Computing
Jupyter(8), Zeppelin(8)
Shell
PowerShell(7), Bash(6)
Relevant Coursework
Spring 2018:
Machine Learning for Trading
Fall 2017:
Design and Analysis of Algorithms
Project Design and Technical Communication
Summer 2017:
Intro to Artificial Intelligence and Machine Learning
Systems Architecture
Fall 2016:
Data Structures and Algorithms
Objects and Design
Discrete Mathematics
Multi variable Calculus
Spring 2016:
Applied Combinatorics
Object Oriented Programming in java
Fall 2015:
Linear Algebra and Abstract Vector Spaces
Introduction to Functional Computing in python
Hackathons:
CodeDay Atlanta 2016
Citi - Security Analytics
- Leveraged Splunk as well as machine learning tool kits such as Scikitlearn to create real time machine learning models and visualizations capable of detecting anomalies, malware, and risks in internal network usage
- Created an internal Alexa application capable of examining and relaying best and worst internal client portfolio information
- Created a workshop using Jupyter notebook detailing how to use Plotly's Python API as well as Pandas and Numpy in order to create 3D visualizations
- Conducted 2 workshops teaching students with little python experience how to import, filter, and display data
- Student reviews on workshop averaged 4+/5
- Gained a basic understanding of how to use different visualization and analytical tools such as SAS, Tableau, and D3
- Created a customer segment identification engine that utilizes PySpark in a Hadoop Environment and Chick-fil-A customer data to identify customers and tailor marketing strategies
- Groomed a dataset of 1 million people using the Chick-fil-A One app, and clustered them based on ordering behavioral patterns
- Untilized technologies such as EMR, Spark, Hadoop, Zeppelin, S3, Plotly, SparkML, SQL, Pandas, Numpy
- Used map reduction formulas (K-Clustering) to process large amounts of data, and group people based on their ordering patterns and demographic data
- Successful results prompted the increase in funding to purchasing and using customer data for enterprise solutions
- Configured (using Bash scripts) and utilized an Elastic Map Reduce (EMR) environment for distributive data processing
- Used Principal Component Analysis on 70+ columns to visualize segments in a 3D space using Plotly
- Plot of customer segments after PCA reduction: plot.ly/~jeremy.dibattista/10.embed
Spring 2017 Internship with IT at Chick-fil-A
- Created a speech detection bot that can assist, display, respond and access in store operations and sales data in real time
- The flow of the bot is as follows: A directive to an Alexa enabled device kicks off a request to an Alexa skill model. This then identifies the intent and kicks off a NodeJS Lambda function held in AWS. This lambda function then processes the language, and formats an output directive. It stores the intent and information additionally in a DynamoDB table. This information stored in the DynamoDB table is then pulled by a web application that can display additional information.
- Worked with in-store Production APIs to allow questions about on the clock employees, and daily sales and operating efficiency
- Allowed for questions such as menu recipes, holding times, ingredient logs, and equipment usage repairs and cleaning
- Essentially we created a more robust, free form, and Chick-fil-A specific version of the Amazon Show
- My role on the team was formatting the skill model, lambda, and dynamo table. (Angular web app pursued by teammates)
- Speech bot was leveraged to gain an additional increase in innovation spending from Chick-Fil-A executives
- The final presentation of the design leveraged funding to an innovation center in Midtown Atlanta. Presentation was seen by the former CIO of Google X, as well as Chick-fil-A's CEO, CIO, and other leadership.
- Will be presented in a restaurant of the future showcase to all Chick-fil-A operators in February 2018
- cfa-certified-trainer-webapp-new.s3-website-us-east-1.amazonaws.com/
- Wrote Machine learning algorithms (Ridge Regression) to detect and predict trends in item sales data
- This supervised machine learning used product mix data and sklearn Python algorithms, and was generally was able to give the accurate number of a specific items sold in the next 2 weeks within a 5% margin
- Wrote scripts for a conversational order taker AI using Python natural language toolkits and Levenshtein distance formulas
- Wrote portions of the conversation flow. In addition, gained an adept understanding of natural language processing in breaking down sentences to find meaning and continue conversation flow.
- Currently spending free time exploring creating educational software as a learning experiment that will utilize machine learning to better cater to student needs
- Project includes use of skills such as Flask, AngularJS, PostgreSQL, SQLAlchemy
- My Clean Water Reporting system project was created in my object oriented design course.
- Full multi windowed javaFX application and utilizes full database storage to retrieve reports and users, bit-string token hashing for security, google maps API integration, and use of lambda filtering expressions that work to display accurate FX charts for viewing data.
- View this project at: github.com/cs2340-group21/cleanwater
Relevant Technologies
(most to least experienced, rated 1 to 10)
Languages
Python(10), JavaScript(7), Java(7), SQL(6), HTML(6), CSS(6), C(2)
Advanced Analytics
PySpark(9), Scikitlearn(8), SplunkML(8), Hadoop(5)
Natural Language Processing
Alexa SDK (9), Fuzzy Levenshtein(9), NLTK (7), Lex(4), Polly(3)
Web Development
NodeJS (7), JQuery(7), Flask (6), Express(6), Bootstrap(5), Angular(2)
Cloud Computing
Lambda(8), S3(8), Elastic Beanstalk(7), Elastic Map Reduce(7), Docker(4)
Data Visualization
Plotly(10), Matplotlib(9), Tableau(4), D3(4)
Database
DynamoDB(8), PostgreSQL(5), SQLAlchemy(4)
Interactive Computing
Jupyter(8), Zeppelin(8)
Shell
PowerShell(7), Bash(6)
Relevant Coursework
Spring 2018:
Machine Learning for Trading
Fall 2017:
Design and Analysis of Algorithms
Project Design and Technical Communication
Summer 2017:
Intro to Artificial Intelligence and Machine Learning
Systems Architecture
Fall 2016:
Data Structures and Algorithms
Objects and Design
Discrete Mathematics
Multi variable Calculus
Spring 2016:
Applied Combinatorics
Object Oriented Programming in java
Fall 2015:
Linear Algebra and Abstract Vector Spaces
Introduction to Functional Computing in python
Hackathons:
CodeDay Atlanta 2016