Ryangineer

About Ryan L Buchanan

I am training as a Software Developer, Data Analyst & Machine Learning Engineer.  I am currently enrolled in the Software Technology program at Ogden-Weber Technical College.  I am also acquiring certifications as an ML Engineer & Algorithmic Trader from Udacity.   I have a Masters in Data Analytics, an MBA & an MS in Instructional Design.  I have working knowledge of C#, R, SQL, HTML, CSS, Javascript, Java and Python programming languages.

I have a multi-displinary background including military intelligence, psychology, linguistics, economics, virtual reality & educational technology.  I have worked abroad for ten years with military, universities & vocational schools.   I have working knowledge of Arabic, Chinese & French.  I am very mobile, able to relocate quickly, adapt easily to diverse working conditions & have a current passport.

I have a passion for mathematics, statistics & artificial intelligence.  I am enthusiastic, highly self-motivated & enjoy presenting informative data to decision makers.  I am eager to work with dynamic teams to create high quality products & services.

Data Science Free Diving

Tools - Investigate a property of a machine learning tool or library.

Candidates
• TensorFlow 2.0
• PyTorch
• Keras
Algorithms - Investigate the behavior of a machine learning algorithm.

• Summarize the parameters of the system & the expected influence they have on the algorithm
• Select a range of datasets suited to the algorithm that are likely to elicit varied behaviors
• Select algorithm parameter configurations that will elicit varied behaviors & list the expected behaviors
• Consider the behaviors of the algorithm that could monitored as the algorithm is run over iterations during the update process
• Design small experiments using one or more combinations of datasets, algorithm configurations & behavior measures to answer a specific question & report results
Candidates
• Naive Bayes
• K-Means Clustering - Ooh! with a Unity animation!!!!
• Decision Tree
Datasets - Investigate and characterize a data set or machine learning problem.

Candidates
• Zooniverse
• Dyson Sphere SETI - with a Unity animation!!!!
• Titanic

Non-code Possibilities

Book Review: Your clear presentation of your notes from reading and reviewing a machine learning book.
Coursework: Your clear presentation of your notes and homework for a machine learning related course (such as a MOOC).
Software Review: Your clear presentation and worked examples for using a machine learning related software tool or library.
Competition Participation: You’re clearly presented notes and results for participating in a machine learning competition, such as Kaggle.
Commentary: An essay in response to a machine learning themed blog post or your detailed response to a machine learning related question on a Q&A site like Quora, Reddit Machine Learning or CrossValidated.

Things to add

• Toggle Progress
• Udemy Courses & Certificates
• Helpful Visualizations for why math is so important for
1. Machine Learning
2. Deep Learning
3. Artificial Intelligence

Smashing Resources

• Super Data Science
• Machine Learning
• Deep Learning
• Artificial Intelligence
• Krista King Math
• Trigonometry
• Calculus
• Linear Algebra
• Probabilities & Statistics
• Machine Learning Mastery
• Kaggle