I fell in love with Machine Learning during my Bachelorβs in Data Science and Programming. Since then I could never live without it. Itβs like a puzzle that I enjoy solving, each solution leading to a new discovery. The thrill of uncovering patterns in data and the joy of creating intelligent systems keep me hooked.
Machine learning (ML) is a field of study in artificial intelligence
concerned with the development and study of statistical algorithms that
can effectively generalize and thus perform tasks without explicit
instructions. Recently, generative artificial neural networks have been
able to surpass many previous approaches in performance. Machine
learning approaches have been applied to
large language models, computer vision, speech recognition, email
filtering, agriculture
and medicine , where it is too costly to develop algorithms
to perform the needed tasks.
The mathematical foundations of ML are provided by mathematical
optimization (mathematical programming) methods. Data mining is a
related (parallel) field of study, focusing on exploratory data analysis
through unsupervised learning.
ML is known in its application across business problems under the name
predictive analytics. Although not all machine learning is statistically
based, computational statistics is an important source of the field's
methods.