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Comprehensive mock data science interview covering bot detection on social media, featuring behavioral questions, feature selection, model implementation, dataset creation, and technical details.
Create a Python program to scrape, download, and transcribe podcast episodes using web scraping, NLP, and speech-to-text API, enhancing your portfolio with practical data processing skills.
Comprehensive Python tutorial covering NLP fundamentals, techniques, and state-of-the-art models. Includes practical examples using popular libraries and hands-on implementation of advanced concepts.
Explore real-world data analysis using Python Pandas to analyze a Lego dataset, covering CSV file reading, DataFrame filtering, and data aggregation techniques.
Comprehensive guide to solving eight LeetCode coding problems in Python, covering various algorithms and data structures. Ideal for interview preparation and improving problem-solving skills.
Learn to automate Python scripts locally and in the cloud using cronjobs, Windows Task Scheduler, AWS Lambda, and Cloudwatch. Includes practical examples for scheduling email sending and generating analytics reports.
Learn web scraping with Python to create a Disney movie dataset, covering BeautifulSoup, data cleaning, APIs, and various Python libraries for real-world data science tasks.
Learn Python web scraping with Beautiful Soup, covering HTML basics, data extraction techniques, and practical exercises to build real-world skills in parsing and analyzing web content.
Learn to build and train a CNN for image classification using TensorFlow and Keras. Covers data preparation, model improvement, hyperparameter tuning, and practical applications in Python.
Learn to refactor Python code professionally by abstracting similar parts into classes, improving code architecture, and extending functionality for more complex game levels.
Comprehensive tutorial on Python classes covering creation, methods, inheritance, and advanced concepts like operator overloading. Ideal for mastering object-oriented programming fundamentals.
Learn to generate realistic mock sales data using Python libraries like NumPy, Pandas, and Datetime. Create datasets with varied product purchases, timestamps, and addresses for data science practice.
Comprehensive Python machine learning tutorial covering sentiment analysis using scikit-learn, from data preparation to model evaluation and optimization, with practical examples using Amazon reviews.
Comprehensive tutorial on NumPy: array creation, indexing, mathematics, statistics, and reshaping. Covers basics to advanced topics, with practical examples and problem-solving exercises.
Learn to create line graphs, histograms, pie charts, and box plots using Matplotlib and Pandas in Python. Visualize real-world data from CSV files, including global gas prices and FIFA player statistics.
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