Tshepo Chris
Primary Interests
AI, Machine Learning, Data Science, and Cloud ComputingEducation
Master's degree in computer scienceAlma Mater
Wits UniversityHonors and Awards
Oxford University Press Prize Award, TATA Prestigious Scholarship Award, and Wits University Postgraduate Merit AwardActive Memberships
Golden Key International Honour Society, South African Statistical Association, South African AI Association, and Data Management Association of Southern AfricaProfile
Tshepo Chris, a senior specialist in model operations engineering at Medscheme, completed his studies at Wits University, obtaining a master’s degree in computer science. He holds expertise in AI and advanced analytics, cloud computing, and business process automation and has established frameworks for data and model governance. Recognized for his academic achievements, he has received awards like the Oxford University Press Prize, the TATA Prestigious Scholarship Award, and the Wits University Postgraduate Merit Award. He is involved in both academia and his profession, holding memberships in organizations like the Golden Key International Honour Society, South African AI Association, South African Statistical Association, and Data Management Association of Southern Africa. Additionally, he has authored books that focus on the practical application of AI in finance, healthcare, and economics.
Publications
AI in Medical Sciences and Psychology
Copyright © 2022 Tshepo Chris Nokeri, Apress / Springer Nature Company
Tshepo’s “AI in Medical Sciences and Psychology” explores the use of AI in healthcare and psychology. Professionals can gain the knowledge and skills required to address challenges in ML, computer vision, and NLP. The book explores the use of AI in tasks including disease classification and medical image analysis.
DOI: 10.1007/978-1-4842-8217-5
Econometrics and Data Science
Copyright © 2021 Tshepo Chris Nokeri, Apress / Springer Nature Company
Tshepo’s “Econometrics and Data Science” He expertly bridges the gap between econometrics and data science. He highlights the possibility of using data science techniques to address complex economic challenges and produce solutions. The book equips readers with the necessary skills to construct models capable of interpreting economic data and influencing decision-making.
DOI: 10.1007/978-1-4842-7434-7
Implementing Machine Learning in Finance
Copyright © 2021 Tshepo Chris Nokeri, Apress / Springer Nature Company
Tshepo’s “Implementing Machine Learning in Finance” investigates the application of ML in finance and teaches investment professionals a systematic strategy for using ML for portfolio management. The book explores several methodologies for risk analysis, performance evaluation, and the development of ML models capable of forecasting future investment portfolio results.
DOI: 10.1007/978-1-4842-7110-0
Web App Development and Real-Time Web Analytics with Python
Copyright © 2021 Tshepo Chris Nokeri, Apress / Springer Nature Company
Tshepo’s “Web App Development and Real-Time Web Analytics with Python” teaches how to use Python to create web apps capable of real-time data analysis. The book discusses web development principles as well as methods for seamlessly incorporating ML algorithms into web projects. The book equips readers with the knowledge to build interactive web apps capable of learning and evolving over time.
DOI: 10.1007/978-1-4842-7783-6
Data Science Revealed
Copyright © 2021 Tshepo Chris Nokeri, Apress / Springer Nature Company
“Data Science Revealed” by Tshepo provides an in-depth introduction to data science, covering fundamental approaches like feature engineering, data visualisation, pipeline construction, and hyperparameter tuning. Readers can gain essential skills to extract significant insights from data and build ML models.
DOI: 10.1007/978-1-4842-6870-4
Data Science Solutions with Python
Copyright © 2021, Tshepo Chris Nokeri, Apress / Springer Nature Company
Tshepo’s “Implementing ML in Finance” investigates the application of ML in finance and teaches investment professionals a systematic strategy for using ML for portfolio management. The book explores several methodologies for risk analysis, performance evaluation, and the development of ML models capable of forecasting future investment portfolio results.
DOI: 10.1007/978-1-4842-7762-1
© 2024 Tshepo Chris. All rights reserved.