Mark Braxton

Prospective data analyst with varied skill set in current data industry topics and procedures to make evidence-based, reliable predictions about the world. Strong believer that data story telling is crucial to relay key insights that are often hidden in multidimensional, complex machine learning models.

Course Practical Data Science

The first part of the project involves predicting the eligibility of the bank customers for a loan by using classification algorithms. The second part involves forecasting the stock prices for the next 24 months using time series.

Skills and Tools

Decision Trees, Random Forest, Time Series

Course Machine Learning

The first part of this project involves predicting the house prices based on the features of the locality using regression techniques. The second part involves predicting the loan eligibility of bank customers using classification algorithms to help the bank prevent potential losses, and focus more on eligible customers.

Skills and Tools

Linear Regression, Logistic Regression, kNN

Course Data Analysis & Visualization

The first part of this project involves exploring the auto-mpg dataset by applying dimensionality reduction techniques and visualizing the data in lower dimensions to extract insights. The second part involves segmenting the bank customers to help the bank upgrading the service delivery model and ensure that customers queries are resolved faster

Skills and Tools

PCA, Clustering, tSNE

Course Foundations for Data Science

This project aims to analyze marketing data and address some important business problems/questions related to customer demographics, product preferences, channel performances, etc.

Skills and Tools

Exploratory Data Analysis, Data Visualization, Statistics

Using Databases with Python, University of Michigan, Offered through Coursera:

Skills Learned

Create, Read, Update, and Delete operations to manage databases in SQL

Basics of Object Oriented Python

Understand how data is stored across multiple tables in a database

Utilize the Google Maps API to visualize data