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Overview
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 multi-dimensional 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
Who this course is for
Data Analyst Beginners
Business Analyst and AI Enthusiasts
Python Developers Beginners
Who Is Interested In ML, AI and Other Big Data Engineering
Testimonials
An amazing experience learning the usage of NumPy for data manipulation. It was really helpful! ~ Aduramomi J
An excellent and comprehensive course on very important points and qualifies you for the field. The way of explanation is easy and fun and the examples are excellent ~ Mohamed A
That is very good ~ Sefineh T
It was easy to understand ~ Roselle S
That was really helpful for beginners ~ Masoumeh H
What you'll learn
NumPy For Data Analysis
NumPy For Data Science
Numerical Computation Using Python
How To Work With Nd-arrays
How To Perform Matrix Computation
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
Overview
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 multi-dimensional 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
Who this course is for
Testimonials
What you'll learn
Requirements
Course Content
6 Sections 19 Lectures 2h 3m total length
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