Aaradhya Singh

I am a college student who has immersed myself in the waters of Machine Learning because I have an interest in how machines can learn, improve, and even decide. It all started with the not-so-complicated questions, such as how Netflix suggests shows or how Google auto-completes searches, and before I knew it, I was captivated by the algorithms that make it all possible. In the current stage of learning, I am actively experimenting with fundamental ML featuresets, such as supervised and unsupervised learning, regression models, classification, and clustering. I use Python, NumPy, pandas, scikit-learn, Jupyter Notebook, and I have even begun to experiment with minor projects related to data prediction and pattern recognition. It is a challenge, but satisfying to learn ML in college. It is not a code camp; it is data awareness, model development, hyperparameter optimisation, and critical reasoning concerning the results. I find it particularly appealing how Machine Learning may be utilised in reality: fraud and recommendation engines, healthcare diagnosis and smart assistants. Currently, I spend much time studying the math behind ML, linear algebra, statistics, and probability so I can understand what is going on under the hood. I have also taken part in Kaggle competitions and tutorials, as well as side projects such as predicting student performance and handwritten digit classification with MNIST datasets. I would also like to learn more about deep learning, neural networks, and model deployment in the future to be able to create scale and production-ready applications. I aspire to apply Machine Learning not only as a technical expertise, but as a means of addressing valuable challenges within society. #MachineLearningStudent #MLBeginner #PythonForML #DataScienceJourney #CollegeToML #ScikitLearn #FutureAIEngineer #MLProjects #LearningByBuilding #MLFromScratch #StudentWithPurpose #KaggleBeginner #AIInMaking #MLAlgorithms #DataDrivenFuture