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The programming language can handle Big Data and perform effective data analysis and statistical modelling. Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. How is R Used in Data Science? Accordingly, Caret represents regression as well as classification training.
After that, move towards unsupervised learning methods like clustering and dimensionality reduction. Machine Learning: Data Science aspirants need to have a good and concise understanding on Machine Learning algorithms including both supervised and unsupervised learning. Also Read: How to become a Data Scientist after 10th?
Here are some project ideas suitable for students interested in big data analytics with Python: 1. Kaggle datasets) and use Python’s Pandas library to perform data cleaning, datawrangling, and exploratory data analysis (EDA). Analyzing Large Datasets: Choose a large dataset from public sources (e.g.,
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