sean-atkinson
Data analyst with 12 years of experience in sales and marketing. Fuelled by tenacity and a passion for simplifying the complex.
Toronto, Ontario, Canada
Pinned Repositories
classifying_dna_sequences
This hackathon project aims to use a Convolutional Neural Network (CNN) to accurately identify promoter classes for DNA sequencing, leveraging spatial pattern recognition to enhance genetic analysis.
conversational_ai
This Conversational AI project aims to develop a chatbot capable of open and dynamic conversation, utilizing a knowledge-grounded human-to-human conversation dataset to create engaging and responsive dialogues.
elist_ecommerce_analysis
This project conducts an analysis of an e-commerce retailer, examining sales trends, marketing channels, and operational efficiency metrics to pinpoint opportunities for growth and optimization.
machine_learning_real_estate_forecasting
This initiative focuses on predicting housing prices using regression modeling, creating a regression model specifically designed to provide millennials with an easy-to-use tool to estimate the appropriate cost of a house.
row_health_wellness_program_analysis
This analysis evaluates a tech-forward insurance company's Wellness Reimbursement Program, concentrating on providing recommendations for product and marketing teams and addressing ad-hoc questions to optimize program effectiveness.
web_apis_and_nlp
This project involves collecting Reddit submission posts from r/LiverpoolFC and r/Everton using Pushshift's API, and employing Natural Language Processing (NLP) to train models that can accurately determine the origin of the posts, differentiating between the two football club subreddits.
sean-atkinson's Repositories
sean-atkinson/conversational_ai
This Conversational AI project aims to develop a chatbot capable of open and dynamic conversation, utilizing a knowledge-grounded human-to-human conversation dataset to create engaging and responsive dialogues.
sean-atkinson/classifying_dna_sequences
This hackathon project aims to use a Convolutional Neural Network (CNN) to accurately identify promoter classes for DNA sequencing, leveraging spatial pattern recognition to enhance genetic analysis.
sean-atkinson/elist_ecommerce_analysis
This project conducts an analysis of an e-commerce retailer, examining sales trends, marketing channels, and operational efficiency metrics to pinpoint opportunities for growth and optimization.
sean-atkinson/machine_learning_real_estate_forecasting
This initiative focuses on predicting housing prices using regression modeling, creating a regression model specifically designed to provide millennials with an easy-to-use tool to estimate the appropriate cost of a house.
sean-atkinson/row_health_wellness_program_analysis
This analysis evaluates a tech-forward insurance company's Wellness Reimbursement Program, concentrating on providing recommendations for product and marketing teams and addressing ad-hoc questions to optimize program effectiveness.
sean-atkinson/standardized_test_analysis
This project conducts an analysis to determine whether the state of California should do away with standardized testing, evaluating the potential benefits and drawbacks through a comprehensive examination of educational practices and outcomes.
sean-atkinson/web_apis_and_nlp
This project involves collecting Reddit submission posts from r/LiverpoolFC and r/Everton using Pushshift's API, and employing Natural Language Processing (NLP) to train models that can accurately determine the origin of the posts, differentiating between the two football club subreddits.
sean-atkinson/bayes_theorem
In this mini-project, I engage in solving practice problems related to probabilities before transitioning to explore various statistical distributions.
sean-atkinson/bayesian_modeling
This mini-project applies Bayesian statistics to baseball data, using prior information and observed statistics to create posterior probabilities.
sean-atkinson/classification_model_validation
This mini-project is an attempt to predict chronic kidney disease in patients using classification modeling, employing statistical techniques to identify risk factors and forecast the likelihood of the disease.
sean-atkinson/clustering_kmeans
This mini-project involves clustering data using the unsupervised k-means algorithm, grouping similar data points together to uncover patterns and insights.
sean-atkinson/cnn
This mini-project involves classifying clothing images using a Convolutional Neural Network (CNN), employing spatial hierarchies and filters to identify and categorize various types of apparel.
sean-atkinson/comparing_classification_models
This mini-project entails end-to-end work on a data science problem, utilizing various classification models to determine whether psychological factors can contribute to predicting left-handedness in individuals.
sean-atkinson/correlated_data
A mini-project tackling a series of correlated data problems, analyzing the interdependencies between variables to derive meaningful insights.
sean-atkinson/fnn
This mini-project utilizes a Feedforward Neural Network to accurately identify digits from a dataset comprising tens of thousands of handwritten images, demonstrating the model's capability in pattern recognition.
sean-atkinson/linear_regression_sacramento
This mini-project involves conducting linear regression analysis, utilizing Sacramento real estate data, to identify relationships and trends between variables within the housing market.
sean-atkinson/model_validation_citi_bike
In this mini-project, I engage in statistical modelling and model validation with Citi Bike data, utilizing mathematical methods to discern patterns and forecast trends.
sean-atkinson/nlp_naive_bayes
This mini-project explores the use of Natural Language Processing (NLP) and the Naive Bayes algorithm to analyze Facebook statuses, investigating whether they can be predictive of a person's agreeableness, in the context of data practices like those employed by Cambridge Analytica.
sean-atkinson/pca
This mini-project applies Principal Component Analysis (PCA) to speed dating data, reducing dimensionality to identify key factors influencing dating preferences and outcomes.
sean-atkinson/probability_challenges
In this mini-project, I tackle a series of probability problems, diving into mathematical challenges to unravel solutions for different probabilistic situations.
sean-atkinson/python_ladder
This mini-project consists of a series of Python coding challenges that become increasingly difficult, testing and enhancing programming skills through progressive complexity.
sean-atkinson/rnn
This mini-project focuses on text classification using a Recurrent Neural Network (RNN), applying sequential learning to categorize text into predefined classes or groups.
sean-atkinson/scala_apache_spark
This mini-project involves the design and implementation of predictive models using Apache Spark, leveraging its distributed computing capabilities for efficient data processing and analysis.
sean-atkinson/sean-atkinson
My personal repository
sean-atkinson/statistical_distributions
In this mini-project, I explore statistical distributions by having fun with loot boxes, analyzing the probabilities and patterns that govern their behaviour and outcomes.
sean-atkinson/supervised_learning_models
This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.
sean-atkinson/time_series
This mini-project focuses on forecasting Walmart store sales using time series analysis, leveraging historical data to predict future sales trends.
sean-atkinson/titanic_eda
This mini-project focuses on exploratory data analysis using the Titanic manifest, delving into the details and characteristics of the data to uncover insights and patterns related to the historic voyage.
sean-atkinson/web_scraping
This mini-project involves web scraping using Beautiful Soup, extracting and manipulating data from websites to gather specific information for analysis or utilization.