Arif Hossin

Skills

• Machine learning +

Machine learning

1. Proficiency in Python Syntax, Data Structures, Functions, and Modules:
2. • Proficiency in Python syntax, including knowledge of basic language constructs like variables, data types, loops, conditional statements, and functions.
   • Understanding of Python's built-in data structures such as lists, tuples, dictionaries, sets, and strings.
   • Ability to write reusable and modular code by defining functions and organizing code into modules for better code organization and reusability.
   • Knowledge of object-oriented programming (OOP) concepts in Python, including classes, objects, inheritance, encapsulation, and polymorphism.
3. Experience with Python Libraries and Frameworks:
   • Familiarity with popular Python libraries and frameworks for various applications:
     • NumPy: A powerful library for numerical computing in Python, providing support for multi-dimensional arrays, mathematical functions, and linear algebra operations.
     • pandas: A data manipulation and analysis library, offering data structures like DataFrame for handling structured data and tools for data cleaning, transformation, and analysis.
     • Django: A high-level web framework for building web applications quickly and efficiently, following the Model-View-Template (MVT) architectural pattern.
     • Flask: A lightweight and flexible web framework for building web applications with minimal dependencies, suitable for small to medium-sized projects and APIs.
   • Experience in using these libraries and frameworks for various applications including web development, data analysis, scientific computing, machine learning, and more.
   • Ability to leverage Python's ecosystem of third-party libraries and packages for specific tasks and domains, enhancing productivity and efficiency in development workflows.

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