I am a professional Machine Learning Software Engineer who loves to explain difficult concepts in easy to understand ways. I teach Data Science and Machine Learning.
My sessions consist of introducing the mathematical theory behind a concept before applying it in python together. I would then set a couple of practical tasks based on the theory for you to complete and we would work through any difficulties together.
My time studying at Cambridge University has given me a lot of experience in what is required for a highly effective one-on-one tutoring session. I use these experiences to tailor my sessions to be as effective as possible for the student.
I set coding projects between sessions and these are reviewed at the start of each session. I also encourage the student to seek out their own unique coding projects to develop their own professional resume and I help them progress in these projects.
Most importantly, I foster an interest in Data Science and coding in the student that will persist beyond our sessions together.
My sessions are fun and interesting and there is never any pressure on the student, I think that a student should learn as much as he/she wants to and at a pace that they're comfortable with.
My aim is for the student to enjoy my sessions greatly and develop an interest and liking for the subjects. I love coding in my job and I want my students to love coding too :)
Currently I work as a Machine Learning Software Engineer where I use deep learning to improve ultrasound scanning.
Before my current job I was working as a Data Scientist for a company where I used python to work with athlete performance and e-commerce data.
I studied Natural Sciences at Cambridge University to masters level .
During my career I have worked with
* Data Science
* tensorflow and keras
* Software Engineering
Intelligent Ultrasound, CF14 4UJ
(March 2020 – present)
Machine Learning Software Engineer
I utilise cutting-edge Artificial Intelligence (AI) in the field of computer vision in order to improve ultrasound scanning.
• Deep learning applied to medical image data using tensorflow and keras
• Implementation of state of the art convolutional neural network architectures
• Image processing and manipulation with opencv and numpy
• implementation of linear algebra techniques using numpy
• Use of AWS cloud services and Sagemaker ML platform
• Version control using SVN
• Communicating with Key stakeholders and clients
MyLife Digital, BA2 2AF
(Sept 2018 – March 2020)
Utilised Data Science techniques to gain insight into E-commerce, sport and permissions data.
• Applying supervised and unsupervised machine learning models in python
• Data cleaning, preparation and feature generation/selection
• Implementation of dimensionality reduction techniques
• Deploying of ML models with Docker
• Building node services
• Use of Microsoft Azure cloud service
• Interactive and static data visualisations
• Interaction with SQL and MongoDB databases
• Version control with Git
University of Cambridge
(2017 – 2018)
2:1 MSci Biochemistry
University of Cambridge
(2014 – 2017)
2:1 BA (Hons) Biological Natural Sciences
Marlwood School, BS35 3LA
• Mathematics – A*
• Biology – A*
• Chemistry – A*
• Physics - A
Application of machine learning in the field of Mesolithic Archaeology
Github project link:
I am collaborating with a researcher in the field of archaeology, we have successfully applied machine learning techniques in order to classify artefacts to their sources and will soon be submitting a paper to scientific journals.
• Supervised machine learning can be used to classify flint artefacts to their source bedrock quarries with strong model performances.
• Dimensionality reduction techniques such as t-SNE and PCA show differences in geochemistry between flints from different sources.
• To create machine learning pipelines that process and model mass spectrometry data in python
• To evaluate several machine learning models in a robust manner
• To create a web application that serves 3D visualisations of dimensionality reduction technique outputs
Deployment of machine learning models with node microservices
Github project link: ((concealed information)
I am collaborating with a full stack developer to create a solution for deploying machine learning models. I am using node services, docker and python to achieve this.
MOOCs, seminars and private tuition
I have acquired a good knowledge of the mathematics underlying machine learning models by delivering and listening to weekly Data Science seminars in my work. I also do a number of online MOOC courses such as the Stanford University CS299 course in Machine Learning, Udemy and Coursera courses.
If Python notebooks fail to render when viewed on Github please copy the URL of the notebook to this notebook viewer to view: (concealed information)
Perfect! Robert is a dedicated tutor who prepares well for the sessions and takes students along a syllabus that works for them. Allows you too practise and learn whilst in lesson.
Perfect! Well prepared tutor who perfectly understood what I was after and has delivered.
Jesus is a highly capable student who learns very effectively by asking important and relevant questions during the learning process. he completes tasks to the best of his ability and to a high standard, I would thoroughly recommend him as a student to other tutors
Perfect! Robert has a deep understanding of python. He took the time to find out what I know and don't know about the foundational stuff before moving on to more complex topics. I would definitely recommend Robert
very capable and picked up concepts very quickly. Friendly and easy going, a great student
Robbie is an excellent tutor. He helped me over the course of 6 months with aspects of Machine Learning using Python for my PhD research, which we have since gone on to produce as a journal article. Robbie has a great ability to break complex topics down and explain them succinctly and in an intuitive way to understand. He is patient and friendly, as well as passionate and engaging. I would definitely recommend him as a tutor!
As a professional software engineer who has known Robert for years and seen some of his work, I can say that he is a highly talented data scientist and programmer. He has strong Python skills and excels in the field of machine learning.
He has a passion for teaching others and is good at communicating technical concepts in easy to understand terms.
Having known Robert five years ago since the start of University, I am both very confident in his ability to teach python to any level and in his capacity to build a friendly teaching environment. He is well-versed and competent in the language and has helped explain concepts to me on many occasions. Robert's strength is his visual teaching style; he explores problems by creating diagrams that illustrate his point perfectly. I'm certain he would use these strengths well as a tutor.
I've collaborated with Robert on fun Python and Raspberry Pi side projects, and can testify that as well as having a solid understanding of Python and Programming concepts, Robbie has an unparalleled enthusiasm for knowledge sharing. He's also an easy going guy to talk to, so he will make an excellent tutor.
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