Storytelling with data is a crucial soft skill for AI and data professionals. To ensure that stakeholders understand the technical requirements, value, and impact of data science team efforts, it is necessary for data scientists, data engineers, and machine learning (ML) engineers to communicate effectively. This post provides a framework and tips you can adopt to incorporate key elements of…
]]>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 people learn about data science, machine learning, and AI and is the initiator of the popular #66daysofdata movement. Currently, Jee works as the Head of Data Science at Scouts Consulting Group. In this post, he discusses his work as a…
]]>Computer vision is a rapidly growing field in research and applications. Advances in computer vision research are now more directly and immediately applicable to the commercial world. AI developers are implementing computer vision solutions that identify and classify objects and even react to them in real time. Image classification, face detection, pose estimation, and optical flow are some…
]]>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 sophisticated algorithms. Nonetheless, practitioners can still benefit from building an understanding and repertoire of algorithms. In this article, the sorting algorithm merge sort is introduced, explained, evaluated, and implemented.
]]>Artificial Neural Networks (ANN) are the fundamental building blocks of AI technology. ANNs are the basis of machine learning models; they simulate the process of learning identical to human brains. Simply put, ANNs give machines the capacity to accomplish human-like performance (and beyond) for specific tasks. This article aims to provide Data Scientists with the fundamental high-level knowledge…
]]>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 background or have only obtained an undergraduate degree in the field of machine learning. Reading academic research papers may be intimidating for individuals without an extensive educational background. However…
]]>Algorithms are commonplace in the world of data science and machine learning. Algorithms power social media applications, Google search results, banking systems and plenty more. Therefore, it’s paramount that Data Scientists and machine-learning practitioners have an intuition for analyzing, designing, and implementing algorithms. Efficient algorithms have saved companies millions of dollars…
]]>Editor’s Note: If you’re interested sharing your data science and AI expertise, you can apply to write for our blog here. Data Science as a discipline and profession demands its practitioners possess various skills, ranging from soft skills such as communication, leadership to hard skills such as deductive reasoning, algorithmic thinking, programming, and so on. But there’s a crucial skill…
]]>Editor’s Note: If you’re interested sharing your data science and AI expertise, you can apply to write for our blog here. Primarily the dual purpose of writing has been to preserve and transfer knowledge across communities, organizations, and so on. Writing within the machine-learning domain is used for the sole purposes mentioned. There are prominent individuals that have placed immense time…
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