Python for Decision Makers and Business Leaders Transcripts
Chapter: Data science in Python
Lecture: Python and data science
Login or
purchase this course
to watch this video and the rest of the course contents.
0:00
You should be aware by now that Python and data science
0:03
go together so well
0:05
and it's one of the fastest growing parts of Python.
0:09
In fact, in that survey I showed you
0:10
in the web development side
0:12
the Python software Foundation survey along with JetBrains
0:15
they also ask, Are you a web developer
0:18
a data scientist, or other?
0:20
Web developer and data scientist, those were about equal
0:23
so this is a huge part of Python
0:25
and I think this is one of the areas
0:27
as I mentioned in the full spectrum section
0:30
that is really unique for Python.
0:32
People can come from other disciplines
0:34
from say science, or engineering, or economics
0:38
and they can come into Python
0:39
and they can do this type of work
0:41
that we're about to talk about
0:42
because Python is so easy to get started.
0:45
But they can do real honest to goodness work
0:48
that has incredible implications
0:50
as far out to the boundaries of science as you want to think.
0:54
How far out? Well, what if we're using telescopes?
0:57
Yes, astronomers all over the world
0:59
use Python to study all sorts of things.
1:02
To study stars, to look for exoplanets
1:05
there's a whole bunch of libraries.
1:08
One of them, the most popular one, is called Astropy.
1:11
So this is a whole project
1:12
for just doing astronomy with Python.
1:15
What was the biggest discovery in astronomy recently?
1:18
Well, as a non-astronomer, just looking in from the outside
1:22
it was probably the fact
1:23
that the very first picture of a black hole was taken.
1:27
This is not as easy as it sounds.
1:30
This doesn't just mean better cameras that can focus more.
1:34
There's all sorts of reasons that it's very hard
1:36
to actually get a clear, true picture
1:39
of what a black hole looks like.
1:40
So the people worked on this project
1:43
they actually used machine learning to try to figure out
1:46
what the real image looked like
1:48
and tried to piece it back together from a bunch of parts
1:51
with many interpretations
1:52
but they taught the machine learning model
1:53
what the most likely outcome was, and they recreated it.
1:58
They use a whole host of libraries
2:00
that are from the data science side of Python
2:02
NumPy, SciPy, pandas, Jupyter, Matplotlib
2:06
and Astropy, of course.
2:09
This is just one discipline, and one huge discovery.
2:12
It would not surprise me if a Nobel Prize
2:15
came out of this work done with Python.
2:18
But speaking of Nobel Prizes
2:19
people did win the Nobel Prize
2:21
for finding the Higgs boson at the Large Hadron Collider.
2:24
Yeah, Python was also involved in that as well.
2:27
Data science and Python, they go really well together
2:30
and it's partly because of this full spectrum language.
2:32
It's so easy to come in as a non-developer
2:34
pick up the little bits you need
2:36
and just keep going, and going, and going
2:38
until you've all of a sudden
2:39
used machine learning and artificial intelligence
2:41
to recreate the picture of a black hole. Wow.