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Learn to build datasets by scraping web pages using Python, Beautiful Soup, and requests. Covers HTML parsing, data extraction, and CSV exporting with pandas.
Learn hands-on Git and GitHub basics, from setup to forking, committing, and syncing repositories. Master version control for efficient collaboration and code management.
Master efficient data manipulation techniques using dplyr in R. Learn powerful functions for faster, more intuitive data analysis and transformation.
Explore key machine learning concepts, including confusion matrices, ROC curves, and AUC. Apply knowledge to real-world challenges and text analysis.
Comprehensive guide to scikit-learn for machine learning in Python, covering model training, selection, evaluation, and text processing. Ideal for beginners and intermediate users.
Master data analysis using pandas: manipulate, visualize, and extract insights from tabular data through hands-on exercises with real datasets and expert guidance.
Discover efficient data science techniques using pandas, covering tasks like group comparisons, handling missing values, and creating insightful plots with real-world datasets.
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