Fast Numerical Computing with Python
.MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 3h 17m | 618 MB
Instructor: Manja Bogicevic

Get to grips with aspects of numerical computing and understand NumPy, the powerful numerical computing module, using Python!
Learn
Develop a strong foundation for numerical computational problems
Competently program in Python and code in Jupyter Notebooks
Use the most significant numerical computing library available for Python: NumPy
Gain high-level access to extremely efficient computational routines with NumPy
Use Python for data science: to work with high-level mathematical functions and simplify data
Implement multi-dimensional arrays and matrices with NumPy's powerful data structures to enrich your programming experience
Perform vector and matrix operations using NumPy and linear algebra
Work on real-world datasets to develop a predictive model using simple and multiple linear regression techniques
About
Performing numerical computations using conventional Python methods is inefficient as complex calculations can take their toll on your system's performance. However, NumPy, the core library for scientific computing in Python, helps keep computations fast and lets your system perform efficiently.
This course adopts a step-by-step approach where you learn through live examples. You will learn numerical computations by performing them! Gain the skills you need to become a better Python developer or data scientist. Beginning with NumPy's arrays and functions, you'll master linear algebra concepts, perform vector and matrix math operations, and use NumPy in Python (using quick and easy techniques) to derive numerical results faster and far more easily than with any other tool. You will understand and practice data processing and predictive modeling throughout the course.
By the end of this course, you will have developed a strong foundation in solving numerical computational problems with NumPy. You will also have a really good knowledge of Python and will be ready to advance your career as a Python developer or data scientist.
All the code and supporting files for this course are available at

https://github.com/PacktPublishing/Fast-Numerical-Computing-with-Python

https://github.com/PacktPublishing/Fast-Numerical-Computing-with-Python

https://www.packtpub.com/data/fast-numerical-computing-with-python-video

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