NumPy - for numerical and scientific computing in Python, provides arrays, matrices, and functions for calculations on them. Pandas - for data manipulation and analysis, provides data structures like dataframes and functions to clean, transform, and analyze data. Matplotlib - for creating data visualizations, including line charts, bar charts, scatter plots, and more. Seaborn - for creating more complex and aesthetically pleasing data visualizations than Matplotlib, including heatmaps, time series, and categorical plots. Scikit-learn - for machine learning, provides functions for classification, regression, clustering, and dimensionality reduction. TensorFlow - for building and training deep learning models, including neural networks and other types of models. BeautifulSoup - for web scraping, provides functions for extracting data from HTML and XML documents. Requests - for making HTTP requests, provides functions for sending HTTP requests and handling responses. OpenCV - for com...
Youtube video: https://youtu.be/_uQrJ0TkZlc Website of the trainer https://codewithmosh.com/ Table of content 00:00:00 Introduction 00:01:49 Installing Python 00:06:10 Your First Python Program 00:08:11 How Python Code Gets Executed 00:11:24 How Long It Takes To Learn Python 00:13:03 Variables 00:18:21 Receiving Input 00:22:16 Python Cheat Sheet 00:22:46 Type Conversion 00:29:31 Strings 00:37:36 Formatted Strings 00:40:50 String Methods 00:48:33 Arithmetic Operations 00:51:33 Operator Precedence 00:55:04 Math Functions 00:58:17 If Statements 01:06:32 Logical Operators 01:11:25 Comparison Operators 01:16:17 Weight Converter Program 01:20:43 While Loops 01:24:07 Building a Guessing Game 01:30:51 Building the Car Game 01:41:48 For Loops 01:47:46 Nested Loops 01:55:50 Lists 02:01:45 2D Lists 02:05:11 My Complete Python Course 02:06:00 List Methods 02:13:25 Tuples 02:15:34 Unpacking 02:18:21 Dictionaries 02:26:21 Emoji Converter 02:30:31...
PyCharm and Jupyter Notebook are both popular environments used for Python development, but they have different strengths and use cases. PyCharm is a fully featured Integrated Development Environment (IDE) for Python, which provides a comprehensive set of tools for code editing, debugging, testing, and version control. PyCharm offers advanced features such as code completion, syntax highlighting, code navigation, refactoring, and debugging. PyCharm also has support for web development frameworks, scientific libraries, and database integration, making it a great choice for developing complex Python applications. PyCharm is a paid software, but a community edition is available for free. Jupyter Notebook, on the other hand, is an interactive computing environment that allows users to create and share documents that contain live code, equations, visualizations, and narrative text. It provides a browser-based interface that lets you run code in cells, which can be executed independently and...
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