GRAHAM ELLINSON
Data. Decisions. Learning.
About Me
I am a data and business analyst. I particularly enjoy working with businesses that have previously not taken advantage of data analytics, showing them how to fully leverage, enrich and optimise their data into actionable insights.
I am excited about new challenges as a data scientist or as a data-driven business consultant. I am always happy to have a chat about new ideas and possibilities in the realm of data science.
DATA SCIENCE
Find out below the range of data science fields which I can help you with. I have experience working in each of these fields and am happy to further discuss any of these areas.
BLOG
Read about the personal interactions I have with predictive analytics and data science. Feel free to comment and provide feedback on any of my posts.
SOLUTIONS
Here you will find a small range of different projects and solutions that I have worked with in the past. If you don't see what you are looking for feel free to reach out for more solutions.
My Experiences With Data
This post talks about my personal experiences with data and its applications. In this post I also describe how often it is the small little solutions that can be most helpful.
Machine Learning: It's Applications Within Predictive Modelling
Today in an ever growing data centric world prediction is growing as are the problems to solve. This post goes a little deeper into the different applications of Machine Learning.
Ethical Challenges in NLP
How can developers and users of NLP models be aware of the challenges and ethical issues and take steps to address these issues.
Neuroscience and Artificial Intelligence
How can Neuroscience inform Artificial Intelligence research and practice, what are the benefits and challenges involved.
The power of recursion
This post demonstrates the power of recursion and uses a few small lines of code that is able to crack even the hardest of the sudoku puzzles.
Enigma Simulation
This post demonstrates the fundamental flaw within the nazi enigma code and illustrates how the allies where able to crack it.
Classification: Detecting Credit Card Fraud
This project shows how a classification model on data collected on credit cards from September 2013, can be used to obtain a 99% accuracy rate to detect fraud.
Regression Analysis (Part One)
This project introduces the basics of regression analysis. It begins with how data pre-processing is carried out. It then step by step builds a model to predict the price of a diamond.
Regression Analysis (Part Two)
This is the second part in the regression series. It takes the same dataset as part one and uses advanced regression methods such as ridge and lasso regression to improve upon the prediction.
Modelling Count Data
This post explains the problems encountered with count data. It provides a local authority with actionable advice how to allocate resources to prevent forest fires.
Forecasting Stock Prices
This project explains the mathematical processes that are used when modelling and forecasting stock prices. It then uses the stock Diageo to demonstrate these models.
Modelling A Startups Profitability
This project models the profitability of a startup business. It clearly explains the mathematical concepts behind the models used and then demonstrates the models on the startup.
Machine Learning
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
Data Visulisation
Data visualization is the graphic representation of data. It involves producing images that communicate relationships among the represented data to viewers of the images.
Data Mining
Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.
Data Protection
Data protection is the process of safeguarding important information from corruption, compromise or loss. The importance of data protection increases as the amount of data created and stored continues to grow at unprecedented rates.
Quantitative Analysis
Quantitative analysis is the use of mathematical and statistical methods in finance.
Predictive Modelling
Predictive modeling uses statistics to predict outcomes. Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred.
- +972 (0) 58 4103504
- graham@grahamellinson.com
- Tel Aviv, Israel
I typically reply to all email inquiries within 24 hours.