Richmond Alake

Richmond Alake is a machine learning and computer vision engineer who works with various startups and companies to incorporate deep learning models to solve computer vision tasks within commercial applications. His involvement within the technology domain spans over five years, from building applications for large conglomerates to integrating AI technology within mobile applications. He's written over 100 articles with over a million views on AI and Machine Learning topics. Richmond believes in the robust application of machine learning to everyday problems and is currently heading several projects that leverage machine learning algorithms and deep learning models to solve ergonomic and social network-related issues.
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Posts by Richmond Alake

Data Science

Data Storytelling Best Practices for Data Scientists and AI Practitioners

Storytelling with data is a crucial soft skill for AI and data professionals. To ensure that stakeholders understand the technical requirements, value, and... 8 MIN READ
Data Science

Advice on Building a Data Science Career: Q&A with Ken Jee

Ken Jee is a data scientist and YouTube content creator who has quickly become known for creating engaging and easy-to-follow videos. Jee has helped countless... 8 MIN READ
Data Science

The Future of Computer Vision

Computer vision is a rapidly growing field in research and applications. Advances in computer vision research are now more directly and immediately applicable... 9 MIN READ
Data Science

Merge Sort Explained: A Data Scientist’s Algorithm Guide

Data Scientists deal with algorithms daily. However, the data science discipline as a whole has developed into a role that does not involve implementation of... 8 MIN READ
Data Science

A Data Scientist’s Guide to Gradient Descent and Backpropagation Algorithms

Artificial Neural Networks (ANN) are the fundamental building blocks of AI technology. ANNs are the basis of machine learning models; they simulate the process... 10 MIN READ
Data Science

How to Read Research Papers: A Pragmatic Approach for ML Practitioners

Is it necessary for data scientists or machine-learning experts to read research papers? The short answer is yes. And don't worry if you lack a formal academic... 12 MIN READ