Senior Data Scientist with over 7 years of international experience in Finance AI scoring systems and risk analysis, specializing in the design and optimization of information systems, loan scoring model, data science, and AI. As a AI researcher, he works on Computer Vision applications to Energy resize and Cache Generated Augmented Architecture applications for protected culture and languages. Arthur Kaza is recognized as a Google Developer Expert in Machine Learning (AI) by Google for his significant contributions to AI in Google communities in his region, with nearly 5 years of experience designing technological learning programs, hackathons, and mentorship. A true technology enthusiast and community leader, he has mentored over 100 young professionals in technological learning programs he managed across Central and East Africa.
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Nov 18, 2025 · 5 min read · Introduction : Quand Votre IDE Préféré Rencontre la Puissance du Cloud Dans l'univers de la data science et du machine learning, les développeurs ont longtemps dû choisir entre deux mondes : travailler dans un environnement cloud comme Google Colab p...
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Jun 2, 2025 · 3 min read · Deduplication has always been a painful, messy, often overlooked process.And yet… in the age of foundation models and large-scale training data, one silent killer keeps haunting your models: duplicated data. I ran into this issue again recently while...
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Dec 21, 2024 · 5 min read · AI and machine learning (ML) are constantly evolving, leading to a flood of new tools and techniques. This rapid pace of change can make it difficult to keep up and understand the nuances of ML concepts. In this article, we aim to clarify some common...
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Oct 6, 2023 · 9 min read · A tree-based modeling package utilizing Keras API within Tensorflow that what we call TensorFlow Decision Forest. Why do you need to read this article, trust me if you are preparing for the Google ML Engineer Exam (The best one for ML Engineer in the...
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Oct 3, 2023 · 9 min read · Every machine learning (ML) practitioner eventually realizes that building a model in a Google Colab Notebook is only a small portion of the overall endeavor. The real thing is preparing a pipeline that transforms your data from its unprocessed state...
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