Numba makes Python/NumPy code runs faster. It achieves this by compiling your Python code into native machine code.

For the uninitiated Numba is an open-source JIT compiler that translates a subset of Python/NumPy code into an optimized machine code using the LLVM compiler library. In short Numba makes Python/NumPy code runs faster. It achieves this by compiling your Python code into native machine code. Before going into Numba details lets understand what are the problems with NumPy and how does Numba solves them. NumPy does not run in parallel. On the other hand Numba fully utilizes the parallel execution capabilities of your computer. NumPy functions are not going to use multiple CPU cores, never mind the GPU. You become dependent on NumPy functions as it is very difficult to write optimal custom NumPy ufuncs (universal functions). Other alternative is to write them in native Python but looping over individual array elements in Python is very slow.

ðŸ”µ Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...

This video on Data Science with Python full course will make you understand the basics of data science, important libraries in Python for Data Science such as NumPy, Pandas, and Matplotlib. You will get an idea about the DS concepts along with mathematics, statistics, and linear algebra.

A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start?

Should I learn about data science, machine learning, or AI? Is there really a difference? This summary gave you a better sense of where to get started.

Applied Data Analysis in Python Machine learning and Data science, we will investigate the use of scikit-learn for machine learning to discover things about whatever data may come across your desk.