Master Python With NumPy For Data Science & Machine Learning
Description
Hi, welcome to the ‘NumPy For Data Science & Machine Learning’ course. This forms the basis for everything else. The central object in Numpy is the Numpy array, on which you can do various operations. We know that the matrix and arrays play an important role in numerical computation and data analysis. Pandas and other ML or AI tools need tabular or array-like data to work efficiently, so using NumPy in Pandas and ML packages can reduce the time and improve the performance of the data computation. NumPy based arrays are 10 to 100 times (even more than 100 times) faster than the Python Lists, hence if you are planning to work as a Data Analyst or Data Scientist or Big Data Engineer with Python, then you must be familiar with the NumPy as it offers a more convenient way to work with Matrix-like objects like Nd-arrays. And also we’re going to do a demo where we prove that using a Numpy vectorized operation is faster than normal Python lists.
So if you want to learn about the fastest python-based numerical multidimensional data processing framework, which is the foundation for many data science packages like pandas for data analysis, sklearn, scikit-learn for the machine learning algorithm, you are at the right place and right track. The course contents are listed in the “Course content” section of the course, please go through it.
I wish you all the very best and good luck with your future endeavors. Looking forward to seeing you inside the course.
Towards your success:
Pruthviraja L
What I will learn?
- After completing the course students can able to learn and get skillful knowledge on:
- NumPy For Data Analysis
- NumPy For Data Science
- Numerical Computation Using Python
- How To Work With Nd-arrays
- How To Perform Matrix Computation
Topics for this course
Introduction-Installation and Setup
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03:30
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How To Install And Setup NumPy & Pandas
07:01 -
How To Work With The Jupyter Notebook
16:56
NumPy Basics
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Numpy Initialization
07:55 -
Creating An Ndarrays
09:24 -
Data Types
06:41 -
Pseudorandom Number Generation
07:54 -
Course Material (Includes Jupyter Notebooks For Practice)
00:00
Indexing In NumPy
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Indexing And Slicing
14:36 -
Boolean Indexing
06:47 -
Fancy Indexing
06:28
File Handling In NumPy
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How To Save And Load In Numpy
03:34
Numerical Computation In NumPy
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Mathematical & Statistical Methods
05:14 -
Arithmetic Operations
05:17 -
Universal Functions In Numpy
08:12 -
Conditional Logics In Numpy
04:37 -
Linear Algebra
04:10
Boolean Arrays and Sorting In NumPy
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Methods Applied To Boolean Arrays
02:52 -
Sorting In Numpy
01:55 -
Unique and Set Logic In NumPy
04:09
About the instructors
Student Ratings & Reviews
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LevelIntermediate
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Total Enrolled47
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Duration02 hours 07 minutes
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Last UpdatedJuly 13, 2021
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CertificateYes
All Lurnweb courses come with
- 14-Day Money-Back Guarantee
- Certificate of completion
- Self-paced lectures
Material Includes
- Complete NumPy Course Material in Jupyter Notebook Format
- The PDF File having all the code cells to work Or use as a guide
Requirements
- If students knows Python, that is well & good
- Anaconda Installation to work with the NumPy and Python
- Basic mathematics
- Willing to learn data analysis, data science or numerical computation for programm
Tags
Target Audience
- Data Analyst Beginners
- Business Analyst and AI Enthusiasts
- Python Developers Beginners
- Who Is Interested In ML, AI and Other Big Data Engineering
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