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NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning

Last updated on May 26, 2024 10:56 am
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Description

What you’ll learn

  • Solid foundation in Python programming, data types, loops, conditionals, functions and more
  • Create and analyze projects via Python NumPy, SciPy, Matplotlib & Pandas
  • Clean data with pandas Series and DataFrames
  • Master data visualization
  • Understanding the NumPy library to efficiently work with arrays, matrices, and perform mathematical operations.
  • Go from absolute beginner to become a confident Python NumPy, Pandas and Matplotlib user

Are you eager to dive into the core libraries that form the backbone of data manipulation, scientific computing, visualization, and machine learning in Python? Welcome to “NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning,” your comprehensive guide to mastering these essential libraries for data science and machine learning.

 

NumPy, SciPy, Matplotlib, and Pandas are the cornerstone libraries in Python for performing data analysis, scientific computing, and visualizing data. Whether you’re a data enthusiast, aspiring data scientist, or machine learning practitioner, this course will equip you with the skills needed to harness the full potential of these libraries for your data-driven projects.

 

Key Learning Objectives:

 

  • Learn NumPy’s fundamentals, including arrays, array operations, and broadcasting for efficient numerical computations.
  • Explore SciPy’s capabilities for mathematics, statistics, optimization, and more, enhancing your scientific computing skills.
  • Master Pandas for data manipulation, data analysis, and transforming datasets to extract valuable insights.
  • Dive into Matplotlib to create stunning visualizations, including line plots, scatter plots, histograms, and more to effectively communicate data.
  • Understand how these libraries integrate with machine learning algorithms to preprocess, analyze, and visualize data for predictive modeling.
  • Apply these libraries to real-world projects, from data cleaning and exploration to building machine learning models.
  • Learn techniques to optimize code and make efficient use of these libraries for large datasets and complex computations.
  • Gain insights into best practices, tips, and tricks for maximizing your productivity while working with these libraries.

 

Why Choose This Course?

 

  • This course offers a deep dive into NumPy, SciPy, Matplotlib, and Pandas, ensuring you grasp their core functionalities for data science and machine learning.
  • Practice your skills with coding exercises, projects, and practical examples that simulate real-world data analysis scenarios.
  • Benefit from the guidance of experienced instructors who are passionate about data science and eager to share their knowledge.
  • Enroll once and enjoy lifetime access to the course materials, enabling you to learn at your own pace and revisit concepts whenever necessary.
  • Mastery of these libraries is crucial for anyone pursuing a career in data science, machine learning, or scientific computing.

 

Unlock the power of NumPy, SciPy, Matplotlib, and Pandas for data analysis and machine learning. Enroll today in “NumPy, SciPy, Matplotlib & Pandas A-Z: Machine Learning” and elevate your data science skills. Don’t miss this opportunity to become proficient in these fundamental libraries and enhance your data-driven projects!

Who this course is for:

  • All levels of students
  • Anyone who want to explore the world of Python
  • This course is for you, if you want a great career

Course content

  • Introduction4 lectures • 28min
  • Introduction
  • Python Numpy6 lectures • 46min
  • Python Numpy
  • NumPy Random7 lectures • 53min
  • NumPy Random
  • NumPy ufunc6 lectures • 40min
  • NumPy ufunc
  • Python Pandas5 lectures • 43min
  • Python Pandas
  • Matplotlib11 lectures • 1hr 28min
  • Matplotlib
  • SciPy8 lectures • 1hr 21min
  • SciPy

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