The central object in Numpy is the Numpy array.  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.

This course will cover why using a Numpy vectorized operation is faster than normal Python lists and how to create matrices and arrays.

Course Components

• Python NumPy in Machine Learning & Data ScienceTraining Course
• Data Science for Beginners 4 Books in 1, Park
• Machine Learning Applications Data Science Fundamentals with Python, Paper
• Python for Data Science and Machine Learning, Chan
• Python Programming 3 Books In 1, Test